KR101433882B1 - Biometric sensors - Google Patents

Abstract

A method for evaluating the authenticity of a provided sample for biometric measurements is described. The light scattered from the sample is received. Multiple images are formed and each image is formed from light received in one of the optical conditions. A set of tissue measurements is generated, and each tissue measurement is generated from one of the images. It is determined whether the resulting tissue measurement is consistent with a sample that is an authentic, open biological tissue sample.

Skin area, biometry, sensor, optical conditions, platen, light source, window moving analysis

Description

BIOMETRIC SENSORS

Cross reference of related applications

This application claims the benefit of the filing date of each of the following applications:

U.S. Patent Application No. 11 / 216,006 entitled "COMPARATIVE TEXTURE ANALYSIS OF TISSUE FOR BIOMETRIC SPOUF DETECTION" filed on September 1, 2005, Robert K. Rowe; U.S. Patent Application No. 11 / 458,619 entitled "TEXTURE-BIOMETRICS SENSOR" filed on July 19, 2006, Robert K. Rowe; U.S. Patent Application No. 11 / 458,607 entitled " WHITE LIGHT SPECTRAL BIOMETRIC SENSORS "filed on July 19, 2006, Robert K. Rowe et al.

Technical field

The present invention relates generally to biometrics. More specifically, the present invention relates to a method and apparatus for performing biometric measurement using spectral information.

"Biometrics" generally refers to a statistical analysis of the characteristics of an organism. One category of biometrics includes "biometric identification" and usually operates in one of two modes, which automatically provides identification of people or proves to be called people's identities. The biometric detection technology measures a person's physical or behavioral characteristics and compares the characteristics with pre-recorded similar measurements to determine if there is a match. The physical characteristics commonly used for biometric identification include the face, iris, shape of the hand, the structure of the blood vessels, and the shape of the fingerprint most commonly performed in all biometric identification features. Common methods for analyzing collected fingerprints include optical, capacitive, radio frequency, thermal, ultrasound, and some other less common techniques.

Most fingerprint-picking methods are based on measuring the skin's properties at or near the surface of the finger. In particular, optical fingerprint readers are generally based on the presence or absence of a difference in index of refraction between the sensor platen and the finger located thereon. ("TIR") occurs on the platen due to the air-platen refractive index difference when the fingerprint air is on a particular location on the platen. Alternatively, when an appropriate refractive index skin makes optical contact with the platen, the TIR at this position is "frustrated " with light traversing the platen-skin contact area. The map of the difference in cross-over TIR of the area where the finger contacts the platen forms the basis of a traditional optical fingerprint reader. There are many optical devices that are used to detect this deviation of the optical contact area in optical devices in bright and dark areas. Usually, a single quasi-monochromatic beam is used as the measuring means for this TIR-base.

There is also a non-TIR optical fingerprint sensor. In most cases, these sensors are based on a quasi-monochromatic device for illuminating the front, side, and back of the fingertip, which spreads light to the skin. The fingerprint image is constructed according to the difference in light transmission across the skin-platen boundary of the peaks and valleys. The difference in optical transmission exists depending on the Fresnel reflection characteristic along some intermediate air gap in the bone, which is well known in the art.

Optical fingerprint readers are particularly sensitive to image quality problems due to unfavorable conditions. If the skin is too dry, the refractive index matching to the platen will not work properly and will result in poor image contrast. Similarly, if the fingers are too wet, the fingertips can be filled with water, so that optical coupling occurs across the entire fingerprint area and significantly reduces image contrast. If the finger pressure on the platen is too small or too large, the skin or sensor may be contaminated, the skin may be old and / or old, or it may be too fine for certain racial groups and very young children Similar results can occur if characteristics exist. These results degrade the image quality and thereby impair the overall performance of the fingerprint sensor. In some cases, commercially available optical fingerprint readers include a thin film of soft material, such as silicon, to mitigate these effects and restore performance. As a soft material, damage, wear and contamination of the membrane limit the use of maintenance-free sensors.

Optical fingerprint readers, such as those based on TIR, as well as forms such as capacitance, RF, and others, typically produce images that are slightly affected by non-ideal image conditions that exist during acquisition. The analysis of the tissue characteristics of the image results is thus influenced by the sampling state, which may limit or obscure the tissue characteristics of the human skin. This limits the use of tissue in such a sensing style.

Biometric sensors, especially fingerprint biometric sensors, are susceptible to malfunction due to various forms of fake samples. In the case of fingerprint readers, there are many known methods of providing a fingerprint pattern of an authenticated user that includes an inanimate material type such as paper, gelatin, epoxy, or latex in the reader. Therefore, even if the fingerprint reader is considered to judge the presence or absence of the fingerprint pattern matching with high reliability, it is assured that it is a matching pattern obtained from the live finger of the intention to the whole system, It is important to do.

Other methods of erroneous operation in some biometric sensors may be through replay. In this scenario, the interceptor records a signal from the sensor when an authorized user uses the system. Later, the interceptor manipulates the sensor as the previously recorded authenticated signal enters the system. As a result, it bypasses the sensor itself and gains access to systems secured from biometrics.

A common approach to making biometric sensors that are more robust, safer, and less error-prone is to use the "dual", "combinatoric", "layered" layered "," fused "," multibiometric ", or" multifactor biometric "sensing of a multidimensional signal. In order to provide enhanced security in this way, biomedical techniques can be misleading by combining techniques such as different parts of the body of the body and using techniques that simultaneously malfunction different samples or combined different sensors prevent. Technique is called "tightly coupled" when technology combines in such a way that it looks at the same part of the body.

The accuracy of noninvasive optical measurements of physiological analytes such as glucose, alcohol, hemoglobin, urea, and cholesterol may be adversely affected by deviations in skin tissue. In some cases it is beneficial to combine and measure one or more physiological analysis objects with biometric measurements. Such dual measures have the potential of interest and application in both commercial and law enforcement markets.

Accordingly, there is a general need in the art for improved methods and systems for biometric measurement and evaluation of analytes using multicolor spectral imaging systems and methods.

Thus, embodiments of the present invention provide a method for evaluating the intrinsic properties of a sample provided for biometric measurements. The sample is illuminated in a plurality of distinct optical conditions. The light scattered from the sample is received. A plurality of images are formed, and each image is formed of light received for each of a plurality of distinct optical conditions. A plurality of texture measures are generated, and each tissue measure is generated from each of a plurality of images. It is determined whether or not the generated plurality of tissue measurement values match a sample that is an authenticated, open biological tissue. The tissue measurement may include that the image-contrast measurement is in any particular embodiment.

The illumination of the sample under different optical conditions can be obtained by illuminating the light with a plurality of distinct wavelengths, with a plurality of distinct illumination angles, etc., under a plurality of distinct polarization conditions.

The tissue measurements may be generated in some embodiments by a spatial-moving-window analysis of each of the plurality of images. In some cases, the plurality of tissue measurements may include measurements of image contrast in specific spatial frequencies. For example, when a sample is illuminated with light having a plurality of distinct wavelengths, it can be seen that under red illumination the image contrast is less than the image contrast under blue illumination. Alternatively, it can be confirmed that the image contrast under red illumination is smaller than a predetermined value. Spatial moving-window analysis can in some cases be performed by calculating the moving-window Fourier transform in multiple images. Alternatively, it can be performed by calculating moving-window intensities and moving-window variation measurements of a plurality of images. For example, in one embodiment, the moving-window focused measurement includes a moving-window average value, and the moving-window variation measurement includes a moving-window standard deviation. In another embodiment, the moving-window intensive measurement includes a moving-window average value, and the moving-window variation measurement includes a moving-window range.

The determination of sampled intent can be made by applying multidimensional scaling to map a plurality of tissue measurements up to a point in a multidimensional space. It is possible to determine whether or not the point is in a predetermined region of the multidimensional space corresponding to the sample which is an open and authentic biological organism. In one embodiment, the multi-dimensional space is a two-dimensional space.

In another embodiment, a method of performing a biometric function is provided. The purpose of the individual's skin is illuminated with illumination light. The target skin part is in contact with the surface. The light scattered from the target skin region is received in a plane substantially including the surface. The image is formed from the received light. Image organization measurements are generated from images. The resulting image tissue measurements are analyzed to perform biometric functions.

In certain embodiments, the biometric function includes an antispoofing function; In such an embodiment, the image tissue measurement is analyzed to determine whether the target skin site includes living tissue. In another embodiment, the biometric function includes an identification function; In such an embodiment, the image tissue measurements are analyzed to determine an individual's identity. In another embodiment, the biometric function includes the functions of demographic or anthropometric measurements; In such an embodiment, image tissue measurements are analyzed to characterize an individual's demographics or anthropometric characteristics.

The light scattered from the target skin area may be received by the image detector, and the surface may be the surface of the image detector. Alternatively, the pattern of light can be translated from the plane to an image detector outside the plane without substantial degradation or attenuation of the pattern, where the relayed pattern is received at the image detector . In another embodiment, the light received from the target skin region may be received in a monochromatic image detector or in a color image detector.

In another embodiment, the illumination light is white light. The image may comprise a plurality of images corresponding to different wavelengths. Thus, the image texture measurements may be generated by performing a spatial motion-window analysis of each of the plurality of images. For example, the moving-window Fourier transform can be computed with a plurality of images. Alternatively, moving-window intensive measurements and moving-window variation measurements of a plurality of images can be computed.

When analyzing the image tissue measurements generated to perform the biometric function, the generated image tissue measurements can be compared with the reference image tissue measurements. In some cases, the reference image tissue measurement is generated from a reference image formed from light scattered from a reference skin site, the target skin site being substantially different from the reference skin site. In certain embodiments, when performing biometric functions, the spectral characteristics of the received light are compared to the reference spectral characteristics.

In another embodiment, a biometric sensor is provided. The sensor includes a surface, a lighting subsystem, a detection subsystem, and a computing device. The surface is suitable for contact with the desired skin area. The illumination subsystem illuminates the target skin area when the target skin area is in contact with the surface. The detection subsystem receives light scattered from a target skin site that is received in a plane that substantially comprises the surface. The computing device is coupled to the detection subsystem and has an instruction to form an image from the received light. It also has an instruction to generate an image tissue measurement from the image and an instruction to analyze the image tissue measurement value generated to perform the biometric function.

There are many different biometric functions that can be performed with sensors. In one embodiment, the bio-metering function has an instruction to determine whether the computing device includes a living tissue of a living tissue, and includes a function of preventing fake. In another embodiment, the biometric function includes an instruction to the computing device to determine the identity of the individual from the generated image organization measurements and includes an identification function. In another embodiment, the biometric function has an order to evaluate an individual's demographics or anthropometric characteristics from the image tissue measurements generated in the computing device, and includes demographic or anthropometric features.

In some cases, the biometric sensor further includes an image detector. In one embodiment, the detection subsystem includes an image detector and is configured to receive light scattered from the target skin site in the image detector, wherein the surface is a surface of the image detector. In another embodiment, the image detector is outboard. The optics are configured to relay the pattern of light from the plane to the image detector without substantial degradation or attenuation of the pattern. The detection system includes an image detector and is set to receive the relayed pattern at the image detector. The image detector may, in another embodiment, include a monochromatic image detector or a color image detector.

In some cases, the illumination subsystem is set to illuminate the desired skin area with white light. The instruction to generate an image tissue measurement comprises an instruction to perform a respective spatial motion-window analysis of a plurality of images, wherein the image may be composed of a plurality of images corresponding to different wavelengths. For example, in one embodiment, there may be instructions to calculate a moving-window Fourier transform of a plurality of images, while another embodiment calculates moving-window focused measurements and moving-window variation measurements of a plurality of images I have an order to ask.

In one embodiment, the command to analyze the image tissue measurements generated to perform the biometric function comprises an instruction to compare the image tissue measurements to the reference image tissue measurements. The target skin region is substantially different from the reference skin region and the reference image tissue measurement value can be generated from a reference image formed from light scattered from the reference skin region. In a particular embodiment, the computing device further has an instruction to compare the spectral characteristics of the received light with the reference spectral characteristics when performing the biometric function.

In another embodiment, a biometric sensor is provided. The white light illumination subsystem illuminates a person's intended skin area with white light. The detection subsystem includes a color imager that receives light scattered from the target skin region and receives the received light. The calculation device has an instruction to acquire a plurality of spatially dispersed images of the target skin part from the light received by the color photographing device. A plurality of spatially dispersed images correspond to different volumes of illuminated tissue of an individual. In addition, the computing device has an instruction to analyze a plurality of spatially distributed images to perform a biometric function.

In one embodiment, the biometric function includes a function to block spurious and the command to analyze a plurality of spatially dispersed images includes an instruction to determine whether the target skin region includes a living tissue. In another embodiment, the command to analyze a plurality of spatially distributed images to perform a biometric function includes an instruction to analyze a plurality of spatially distributed images to assess an individual's demographics or characteristics of an anthropometric measurement do. In another embodiment, the instruction to analyze a plurality of images spatially dispersed to perform a biometric function includes an instruction to analyze a plurality of spatially distributed images to determine the concentration of the analyte in an individual's blood do.

In another embodiment, the white light illumination subsystem is suitable for illuminating the desired skin area through the platen, and the biometric sensor further comprises a platen in contact with the desired skin area. In another embodiment, the white light illumination subsystem can be adapted to illuminate the desired skin area when the skin area is not in physical contact with the biometric sensor.

The white light may be provided in different ways in different embodiments. For example, in one embodiment, the white light illumination subsystem includes a broadband white light source. In another embodiment, the white light illumination subsystem includes an optical device for combining light provided by a plurality of narrowband light sources and a plurality of narrowband light sources. The plurality of narrowband light sources may provide light at a wavelength corresponding to each of the primary color sets. In some cases, the illuminated area where the target skin area and the target skin area are illuminated is moved relative to each other.

In another embodiment, the use of polarization can be seen by including a first polarizer in an illumination system that polarizes white light. The detection system includes a second polarizer facing the received light. The first polarizer and the second polarizer may cross each other. In another embodiment, the first polarizer and the second polarizer may be parallel. In another embodiment, the first polarizer may be omitted while retaining the second polarizer. In another embodiment, two or more polarization options can be combined in one device. The detection system may also occasionally include an infrared filter on which the received light is incident before the received light enters the color imaging device.

In certain cases, the target skin area is the bottom surface of the finger or hand, and the biometric function includes biometric identification. The instruction to analyze a plurality of spatially dispersed images includes an instruction to acquire a surface fingerprint or a palmprint image of a target skin region from a plurality of spatially dispersed images. To verify an individual's identity, a surface fingerprint or a long finger image is compared to a fingerprint or a long finger image database. In another embodiment where the biometric function includes biometric identification, the command to analyze a plurality of spatially dispersed images may instead comprise a plurality of spatially distributed images and a database of multicolor spectral images Quot; < / RTI >

In yet another embodiment, a method of performing a biometric function is provided. Personal Purpose The skin area is illuminated with white light. The light scattered from the target skin part is received by a color photographing apparatus in which the received light enters. A plurality of spatially dispersed images of the desired skin region are obtained with a plurality of spatially dispersed images corresponding to different volumes of illuminated tissue of the individual. A plurality of spatially dispersed images are analyzed to perform biometric functions.

In another embodiment, the biometric function includes the function of blocking spurious and analyzing a plurality of spatially dispersed images includes determining whether the target skin region comprises living tissue. In another embodiment, a plurality of spatially dispersed images are analyzed to assess an individual's demographic or anthropometric characteristics. In yet another embodiment, a plurality of spatially dispersed images are analyzed to determine the concentration of the analyte in the blood of an individual.

The target skin area can sometimes be illuminated by directing the white light through a platen that contacts the skin area. In some cases, the target skin area may be illuminated with a broadband white light source, and in other cases, a plurality of narrowband light beams, possibly corresponding to a set of primary colors, may be generated and combined. The target skin region may sometimes move relative to the illuminated area where the target skin region is illuminated.

In one embodiment, the white light is polarized with the first polarized light and the received light scattered from the target skin area is polarized with the second polarized light. The first and second polarizations may be substantially mutually intersecting or substantially mutually parallel. The received light may sometimes be filtered at the wavelength of infrared light before the received light enters the color imaging apparatus.

In some cases, the biometric function includes biometric identification. For example, the target skin area may be the bottom surface of a finger or a hand. Analysis of a plurality of spatially dispersed images can be performed by receiving a surface fingerprint or a long fingerprint image of a target skin region from a plurality of spatially dispersed images and comparing the fingerprint image of the fingerprint or the fingerprint image or the fingerprint image with the database of the fingerprint image. In an alternative embodiment, a plurality of spatially distributed images may be compared to a database of multicolor spectral images to identify an individual.

1 is a front view of a noncontact biometric sensor according to an embodiment of the present invention;

2A is a Bayer color filter array structure diagram that may be used in an embodiment of the present invention;

Figure 2b is a graph showing the color response curves of the Bayer color filter array shown in Figure 2a;

3 is a front view of a non-contact biometric sensor according to another embodiment of the present invention;

Figure 4 is a plan view of the sensor in the form of a sensor for taking data during relative movement between the skin region and the optically active region of the sensor;

Figure 5 is a multicolor spectral data cube that can be used in certain embodiments of the present invention;

6 is a front view of a contact biometric sensor according to an embodiment of the present invention;

FIG. 7A is a side view of a contact biometric sensor in the embodiment; FIG.

FIG. 7B is a side view of the contact biometric sensor in another embodiment; FIG.

8 is a front view of a contact biometric sensor according to another embodiment of the present invention;

9 is a view showing a multicolor spectrum biometric sensor according to another embodiment of the present invention;

FIG. 10A shows a structure of a contact tissue biometric sensor according to an embodiment of the present invention; FIG.

FIG. 10B is a side view of a contact tissue biometric sensor in one form; FIG.

Fig. 10C is a side view of a contact tissue biometric sensor in another form; Fig.

11 is a schematic illustration of a computer system that can be used to manage the functions of contact and non-contact biometrics sensors according to embodiments of the present invention;

12 is a graph of the oxygen-absorbed blood absorbance spectrum;

Figure 13 shows an image of an actual finger and a fake under different lighting conditions;

Figure 14 is a flow chart summarizing a particular method of the present invention;

15A is a result graph taken in the first embodiment of the present invention;

15B is a graph showing a comparison result between the actual finger and the fake data in Fig. 15A;

FIG. 15C is a segregation graph of the multidimensional scaling results of the data of FIG. 15A; FIG.

FIG. 16A is a graph showing a comparison between the actual finger and the fake of the result obtained in the second embodiment of the present invention; FIG.

Figure 16b is a segregation graph of the multidimensional scaling results of the data of Figure 16a;

FIG. 17A is a graph showing a comparison between the actual finger and the fake of the result obtained in the third embodiment of the present invention; FIG.

FIG. 17B is a segregation graph of the multidimensional scaling results of the data of FIG. 17A; FIG.

18 shows a flow chart summarizing a number of different biometric functions that can be performed and summarizing a method of using contact and non-contact biometric sensors;

19 is a flowchart summarizing a method of operating a contact tissue biometric sensor according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

1. Overview

Embodiments of the present invention provide systems and methods for collecting and processing various different types of biometric measurements, including integrated, multi-factor biometric measurements in some embodiments. Such measurements can provide a strong assurance of human identity as well as authentication of the biometric samples taken. In some embodiments, the sensor uses white light passing through a person ' s skin surface and scatters within the skin and / or tissue below. As used herein, "white light" refers to light having a spectral composition that can be separated into components of a wavelength band, which in some cases may include primary colors. The usual primary colors that defined white light were red, green, and blue, however, as such techniques are known in the art, other combinations may be used in other examples. Clearly, "white light" may not appear white to human observers as used herein and may have different light colors or combined colors due to the exact wavelength dispersion and the intensity of the wavelength band components. In other cases, the white light may comprise one or more bands of the ultraviolet or infrared spectral region. In some cases, when white light consists of wavelength bands in the infrared and / or ultraviolet spectral region, white light may not even be visible to human observers at all. Part of the light scattered by the skin and / or underlying tissue is used to escape the skin and form an image of the structure of the tissue at and below the skin surface. Because of the wavelength-dependent nature of the skin, the image formed from each wavelength of light included in the white light may be different from the image formed at other wavelengths. Embodiments of the present invention thus collect images in such a way that characteristic spectra and spatial information can be extracted from image results.

In other applications, it may be desirable to evaluate other elements and characteristics of the body, either independently or in combination with biometric measurements. For example, in one particular embodiment, the ability to measure the level of a person's analyte at the same time as the measurement of the fingerprint pattern is provided. The application for law enforcement can be found in embodiments in which the subject of measurement analysis comprises a blood-alcohol level of a person; Such embodiments also enable a variety of commercial applications, including limiting automotive access. In this method, the identity of the person who is being measured and measured can be linked so that it can not be solved.

Skin composition and organization are very distinct, very complex, and vary from person to person. By performing optical measurements of the spatial spectral characteristics of the skin and underlying tissue, a number of evaluations can be made. For example, the biometric identification function can be performed to identify and verify who has skin being measured, and the survival function ensures that the measured sample is a living, viable skin and not a different kind of material And the assessment may be made up of a variety of physiological factors such as age, gender, ethnicity, and other demographic and anatomic characteristics, and / or measurements may be made of various analytes and alcohol, glucose, Oxidation, bilirubin, cholesterol, urea, and the like.

The complex tissue of the skin can be used in other embodiments to tailor the method or system aspect for a particular function. The outermost layer of the skin is supported by the epidermis, the dermis and the hippie below. The epidermis itself may have five homogeneous sublayers, including the stratum corneum, stratum lucidum, stratum granulosum, stratum spinosum, and stratum germinativum. Thus, for example, the skin below the uppermost stratum corneum has properties related to the surface topography as well as the properties that vary with the thickness of the skin. When the blood supplied to the skin is in the dermis, the dermis has a bump to the epidermis, known as the "dermal papillae", which brings the blood supply closer to the surface through the capillaries. On the bottom surface of the finger, the capillary structure follows the pattern of the friction peaks and valleys on the surface. At other locations in the body, the capillary bottom structure is less orderly, but still has a special location and personality. Moreover, topographical features of the interface between the different layers of skin are quite complex and are characteristic of the skin location and the person. While this light source of the skin and underlying tissue of the underlying tissue implies a significant defective light source for biometric measurements or unimaged optical measurements of the skin for measurement of analytes, Lt; RTI ID = 0.0 > spectral < / RTI >

In some cases, the ink, dye and / or other pigmentation may be expressed as a part of the skin, such as a local coating or a tattoo on the lower surface. Such artificial coloration may or may not appear in the human eye. However, if one or more wavelengths used in the apparatus of the present invention are sensitive to the dye, the sensor may be used in some embodiments to verify the presence, quantity and / or form of the dye in addition to other established measurements.

In general, embodiments of the present invention provide a method and system for collecting spatial spectral information that can be represented in a multidimensional data structure that is independent of spatial and spectral dimensions. In some cases, the desired information is only obtained in a portion of the entire multidimensional data structure. For example, evaluation of a uniformly dispersed, spectrally activated compound may only require the properties of the measured spectrum, which can be extracted from the overall multidimensional data structure. In such a case, the overall system design can be simplified to reduce or eliminate the spatial components of the collected data by reducing the number of image pixels to the limit of one pixel. Thus, while the disclosed systems and methods are generally depicted in an environment of spatial spectral imaging, the present invention finds that similar measurement is included, even to the point where only one detector element is present, where the angle of imaging is significantly reduced.

2. Non-contact biometric sensor

One embodiment of the present invention is depicted in the schematic view of Fig. 1, which shows a front view of the non-contact biometric sensor 101. Fig. The sensor 101 includes a detection subsystem 123 having an illumination subsystem 121 and an imaging device 115 having one or more light sources 103. Although the figure depicts an embodiment in which the illumination subsystem 121 includes a plurality of illumination subsystems 121a and 121b, the present invention is not limited to the number of lights or the detection subsystem 121 or 123 . For example, the number of the lighting subsystem 121 may conveniently be selected to face other structural constraints of the sensor 101 to face the package of requirements, to obtain a certain level of illumination. The illumination light passes through the illumination lens unit 105 that makes the illumination from the light source 103 into a desired shape such as floodlight, light, and light. The illumination lens portion 105 is shown as being made of one lens for convenience, but more generally may include one or more lenses, one or more mirrors, and / or a combination of other optical elements. The illumination lens unit 105 also includes a mechanism (not shown) of the scanner for scanning the illumination light in a specified one-dimensional or two-dimensional pattern. The light source 103 may include a point light source, a linear light source, a planar light source, or may include a series of such light sources in other embodiments. In one embodiment, the illumination light is provided by a linear polarizer 107 through which the light passes before it reaches the fingers 119 or other skin regions of the person being studied, for example with polarized light. Embodiments such as those shown in Figure 1 are referred to herein as "noncontact" sensors because the imaged skin region can be positioned to interact with light without contact to any solid surface. In a "contact" biometric sensor, described in detail below, the imaged skin portion contacts some solid surface, such as a platen or photodetector.

In some cases, the light source 103 includes a white light source that may be provided as a broadband light source or in other embodiments may be provided as a collection of narrowband emitters. Examples of broadband light sources include white light emitting diodes ("LEDs"), incandescent bulbs, or incandescent bars. The collection of narrowband emitters may include a quasi-monochromatic light source having a primary color wavelength as in embodiments including a red LED or laser diode, a green LED or laser diode, and a blue LED or laser diode.

Another mechanism to reduce direct reflected light is the use of optical polarizers. Linear and circular polarizers can be conveniently used to make optical measurements more sensitive to certain skin thicknesses, as is well known in the art. In the embodiment shown in FIG. 1, the illumination light is polarized by the linear polarizer 107. The detection system 123 may also include a linear polarizer 111 that is arranged with an optical axis that is substantially orthogonal to the illumination polarizer 107. In this way, light from the sample undergoes multiple scatterings to significantly change the polarization state. Such occurrences occur when light passes through the surface of the skin and is scattered back to the detection subsystem 123 after many scatter events.

Conversely, the use of the two polarizers 107, 111 can also be used to increase the influence of the directly reflected light by arranging the polarizer 111 substantially parallel to the polarizer 107. In some systems, it may be advantageous to combine two or more polarization configurations into one device that allows collection of multicolor spectral data collected under two different polarization conditions (i. E., Crossed polarization conditions and Under parallel polarization conditions). In another embodiment, the polarizers 107, 111, or both can be omitted, taking into account a collection of substantially randomly polarized light.

The detection subsystem 123 may include a detection lens portion that includes lenses, mirrors, phase plates and wavefront coding devices, and / or different optical elements that cause the detector 115 to form an image. . The detection lens section 113 may also include a scanning mechanism (not shown) for relaying a portion of the overall image to the detector 115 during the process. In all cases, the detection subsystem 123 is sensitive to light that undergoes optical scattering in the skin and / or underlying tissue before it passes through the skin's surface and exits the skin.

In embodiments where white light is used, the detector 115 may include a Bayer color filter array that filters components corresponding to a set of primary colors that are aligned in a Bayer pattern. An example of a pattern, such as alignment, using components of the red 204, green 212, and blue 208 color filters is shown in FIG. In some cases, the detection subsystem 123 may further include an infrared filter 114 that reduces the amount of infrared detected. As in the color response curve in the exemplary Bayer filter arrangement shown in FIG. 2B, there is generally some overlap in the spectral range of the red, green, and blue 228 transmission characteristics of the filter components. As is evident from the transmission characteristic curves of green 232 and blue 228, the arrangement of the filters can take into account the transmission of infrared radiation. This is avoided by the inclusion of the infrared filter 114 as part of the detection subsystem. In another embodiment, the infrared filter 114 may be omitted and one or more light sources 103 emitting infrared radiation may be integrated. In this way, all of the color filter components 204,208, and 212 may be considered to pass substantially through the light, resulting in the infrared image passing through the full detector 115. [

Another embodiment of the non-contact biometric sensor is shown schematically in the front view of Fig. In this embodiment, the biometric sensor 301 includes a lighting subsystem 323 and a detection subsystem 325. [ There may be multiple illumination subsystems 323, as shown in a particular embodiment with two illumination subsystems 323 in FIG. 3, in some embodiments, similar to the embodiment depicted in FIG. 1 similarly. The white light source 303 including the illumination subsystem 323 may be any white light source, including a collection of the above-described broadband light sources or narrowband light sources. The light from the white light source 303 passes through the illumination lens unit 305 and the linear polarizer 307 before passing through the skin region 119. A portion of the light is scattered distally into the detection subsystem 325, which includes the imaging lens portions 315 and 319, the linear polarizer 311, and the dispersion optical element 313 from the skin portion 119. The dispersive element 313 may comprise a one-dimensional or two-dimensional diffraction grating, which may be a transmitted or reflected, prism, or other optical configuration known to cause deflection of the path of light, such as the function of the wavelength of light in the art. In the illustrated embodiment, the first imaging lens section 319 collimates the light reflected from the skin region 119 for transmission through the linear polarizer 311 and the dispersive element 313. The spectral components of the light are separated at an angle by the dispersive element 313 and individually focused by the second imaging lens section 315 to the detector. As discussed in FIG. 1, when the optical axes of the polarizers 307, 311 are substantially orthogonal to each other, the polarizers 307, 311 (including the illumination and detection subsystems 323, 325) Operates to reduce the detection of light that is directly reflected at the detector 317. Polarizers 307, 311 can also make the optical axis substantially parallel, so that detection of light reflected directly at detector 317 increases. In another embodiment, either or both of the polarizers 307 and 311 may be omitted.

The image generated from the light received at the detector is thus "coded" in the form of a computer terrain imaging spectrometer ("CTIS"). Both the spectral and spatial information are present in the resulting image at the same time. The cryptogram of an individual's spectrum is obtained by a "reconstruction" of mathematical inversion or encrypted imaging.

It is noted that the base of the contactless sensor of Figure 1 can be provided for the scanner mechanism to scan the illumination light. This is an example of a more general kind of embodiment with relative movement of the illuminated area and the skin area. In such an embodiment, the image may be constructed by accumulating the separated image portions collected during the relative movement. Such relative movement may also be obtained in an embodiment in which the sensor is set in a read setting, where the user is instructed to relay the skin region. One example of a read sensor is shown in plan view in the schematic view of FIG. In this figure, the illumination area of the sensor 401 and the detection area 405 are substantially co-linear. In another embodiment of the read sensor 401, there may be one illuminated area director. For example, there may be a plurality of illuminated regions arranged next to either side of the detection region 405. In other embodiments, the illumination area 403 may overlap, partially or wholly, with the detection area. The image data is collected by the sensor by relaying a finger or other body part through the optically activated area, as indicated by the arrow in Fig. In some implementations, the read sensor may be implemented in any of the contactless sensor settings depicted above, even if used in contact settings, which will be described in detail below. Continuously received light from a discontinuous portion of the skin region is used to create an image that is later used for biometric applications.

The depicted embodiment provides a major portion of spatial spectral data that can be used in biometric applications depicted below. The present invention does not limit any particular form of critical storage or analysis of spatial spectral data. The point of the explanation is shown in the form of the data cube of Fig. The data cubes 501 are arranged along a spectrum dimension of each of a plurality of planes 503, 505, 507, 509, 511 corresponding to different portions of the optical spectrum and containing spatial information. It looks disassembled. In other cases, the spatial spectral major part may include additional information types besides spatial and spectral information. For example, different illumination conditions, different polarization conditions, etc., defined by different illumination structures can provide additional dimensions of information. More broadly, the data collected under multiple optical conditions is referred to as "multispectral" data, where the data collection is simultaneous or sequential. A more complete description of multicolor spectrum data is described in co-pending U.S. Patent Application No. 11 / 379,945 entitled " MULTISPECTRAL BIOMETRIC SENSORS ", filed April 24, 2006. The above-mentioned patent applications are hereby incorporated by reference in their entirety for all purposes. The spatial spectral data can thus be thought of as a particular type of multicolor spectral data, including different illumination wavelengths with different optical conditions.

In embodiments where the light is illuminated under white light, the images 503, 505, 507, 509, and 511 may include light of 450 nm, 500 nm, 550 nm, 600 nm, And the like. In other cases, there may be three images corresponding to the amount of light in the red, green, and blue spectral bands of each pixel location. Each image represents the optical effect of light of a particular wavelength interacting with the skin. 505, 507, 509, and 511 are generally different from others depending on the optical characteristics of the skin and the skin configuration that varies depending on the wavelength . The data cube can thus be expressed as R (Xs, Ys, Xi, Yi, lambda) and describes the amount of scattered light of wavelength lambda visible at points Xi, Yi respectively when illuminated at points Xs, Ys of the light source do. Different illumination settings (light, line, etc.) can be summarized by adding that point to the point location of the appropriate light source. A traditional non-TIR fingerprint image F (Xi, Yi) can be vaguely described as a multicolor spectral data cube of a given wavelength [lambda] o and adds the positions of all light sources;

Conversely, the spectral biometric data set S ([lambda]) is related to the intensity of light measured at a given wavelength [lambda] on the difference D between the illumination and detection positions:

The data cubes R thus relate to both traditional fingerprint images and spectral biometric data sets. A data cube R is a superset of any one of two different data sets and contains different information that may be lost in either one of two interrelated and disjointed forms.

Light passing through the skin and / or underlying tissue is generally affected by the different optical properties of the skin and / or underlying tissue at different wavelengths. The two optical effects in the skin and / or under the tissue that are affected differently at different wavelengths are scattering and absorption. Optical scattering in skin tissue is generally a smooth, relatively slowly changing functional wavelength. Conversely, absorption from the skin is a strong function of the wavelength, usually due to the specific absorption characteristics of the particular element present in the skin. For example, blood, melanin, water, carotene, ethanol, and glucose all have significant absorption properties in the 400 nm to 2.5 μm spectral region, which can sometimes be included by a white light source.

The combined effect of optical absorption and scattering allows different illumination wavelengths to pass through skin of different thicknesses. This effectively enables different spatial images to have different and complementary information corresponding to illuminated tissues of different volumes. In particular, the capillary layer near the surface of the skin has distinct spatial properties that can be imaged at the wavelength at which the blood strongly absorbs. Because of the complex wavelength-dependent nature of the skin and underlying tissue, the set of spectral values corresponding to a given image location has clear and distinct spectral characteristics. These spectral characteristics can be used to classify the images collected on a pixel by pixel basis. This evaluation can be performed by generating a typical tissue spectral quality from a set of qualifying images. For example, the spatial-spectral data shown in Fig. 5 can be reconstructed into an Nx5 matrix when N is the number of image pixels containing data from living tissue, based on when it is an air-enclosed area . Unique analysis or other factor analysis performed with this set matrix gives rise to representative spectral characteristics of these tissue pixels. The spectra of the pixels in the data set behind can be compared with previously established spectral features using measurement criteria such as Mahalanobis distance and spectral error. If a small number of image pixels have a spectral quality that is inconsistent with a living tissue, then the sample is considered to be rejected rather than intrinsic, and the method incorporating the method of blocking the fake in the sensor based on the living judgment of the sample Mechanism.

Alternatively, the tissue properties of the skin may be combined or alone with the spectral properties used to determine the intrinsic properties of the sample. For example, each spectral image can be analyzed in such a way that the magnitude of the various spatial characteristics can be described. Such methods include Wavelet transform, Fourier transform, cosine transform, gray-level co-occurrence, and the like. The resulting coefficients from any transformation also describe the organization aspect of the image from which they are obtained. The organizational characteristics of the colors of the multicolor spectral data are described as a set of such coefficients obtained from a set of spectral images. These characteristics can be compared with similar characteristics of a known sample to perform biometric measurements such as false or alive judgment. The method of performing such a determination is generally similar to the method described above with the spectral characteristics. The appropriate classification techniques for such judgments include linear and quadratic discriminant analysis, classification trees, neural networks, and other methods well known in the art.

Similarly, in the embodiment where the sample is the bottom surface of a hand or a finger, the image pixels are referred to as "ridge "," valley ", or "other ) &Quot;. This classification can be performed using discriminant analysis methods such as linear discriminant analysis, square discriminant analysis, principal component analysis, neural networks, and other techniques well known in the art. Since the pixels of the peaks and valleys are adjacent to a typical bottom surface, in some cases, data from adjacent neighbors around the image pixel of interest is used to classify the image pixels. In this way, traditional fingerprint images can be extracted for further processing and biometric measurements. The "other" category may indicate an image pixel having a different spectral quality from that expected in the intrinsic sample. In an image classified as "other ", the threshold may be fixed in the total number of pixels. If this threshold is exceeded, the sample is not intrinsic, and appropriate instructions can be given and actions taken to be taken.

In a similar manner, multicolor spectral data collected from areas such as the bottom of a finger are analyzed to directly assess the location of defined " minutiae points ", such as those that undergo peak, bifurcation, or other topographic changes . For example, the quality of the color organization of a multicolor spectrum data set can be judged as described above. This quality can be used to classify each image location as "ridge ending", "ridge bifurcation", or "other" in the same manner as described previously. In this method, detailed feature extraction can be performed using image normalization, image binarization, image thinning, and minutiae filtering, which require tough calculations such as those well known in the art Can be done directly from multicolor spectral data without performing an operation.

The biometric determination of identity verification may consist of using the entire main portion of the spatial-spectral data or using a particular portion thereof. For example, suitable spatial filters can be applied to detect low spatial frequency information, which is typically representative of a tissue that has been activated depth-to-depth in tissue. Fingerprint data can be extracted using similar spatial frequency separation and / or pixel-classification methods disclosed above. The spectral information can separate the active portion of the image in the same manner as discussed above. These three parts of the main portion of the spatial-spectral data can be processed and compared with the corresponding registration data using methods well known in the art for determining the degree of match. Based on the strength of the match of these characteristics, the decision can be made by considering the match of the sample with the registered data. Additional details regarding the nature of the space-spectrum analysis that can be performed are described in U.S. Patent Application No. 10 / 818,698 entitled "MULTISPECTRAL BIOMETRIC SENSOR ", filed April 5, 2004 by Robert K. Rowe et al. ). The above-mentioned patent applications are hereby incorporated by reference in their entirety for all purposes.

As noted previously, certain substances that may be present in the skin and underlying tissues have distinct absorption characteristics. For example, ethanol has characteristic absorption peaks at about 2.26 탆, 2.30 탆, 2.35 탆, and spectrum peaks at 2.23 탆, 2.28 탆, 2.32 탆 and 2.38 탆. In some embodiments, the noninvasive optical measurement is performed at a wavelength in the range of 2.1-2.5 占 퐉, more specifically 2.2-2.4 占 퐉. In an embodiment that includes at least one peak wavelength and one bone wavelength, the spectral outcome data may be used to provide an assessment of the concentration of alcohol in the tissue, as well as providing a biometric signature of the person being examined. least squares, principal-component regression, and other techniques known in the art. The interaction of the blood-alcohol levels may be at a value judged as part of this wavelength, while at least three spectral peak values are tested to obtain a more accurate result than when seven spectral peaks and valleys are measured .

In another embodiment, the noninvasive optical measurement is performed at a wavelength in the range of 1.5-1.93 [mu] m, more specifically in the range of 1.6-1.8 [mu] m. In certain embodiments, optical measurements are performed at one or more wavelengths of about 1.67, 1.69, 1.71, 1.73, 1.74, 1.76 and 1.78. The presence of alcohol is considered at such wavelengths that the spectral peaks are 1.69, 1.73 and 1.76 and the spectral bones are 1.67, 1.71, 1.74 and 1.78. Similarly, in the 2.1-2.5 μm wavelength range, the concentration of alcohol is considered by the relative intensity of one or more spectral peaks and valleys. Also, in order to obtain more accurate results when the seven spectral peaks and bone values are measured, while the interaction of the blood-alcohol levels can be made with values judged to be part of the wavelength in the 1.5-1.9 mu m range, It is preferable to test the spectral peak values of the two spectral peaks.

Small spectral alcohol-monitoring devices may include various systems and applications in particular embodiments. The spectral alcohol-monitoring device may be provided to law enforcement personnel or may be incorporated into a dedicated system such as an electric clock, a wristwatch, a cell phone, a PDA, or any other electrical device, Lt; / RTI > Such devices may include a mechanism to indicate whether the blood-alcohol level of an individual is within a predetermined limit. For example, the device may include red and green LEDs, such as an electrical device in which the green-LED is illuminated if the blood-alcohol level of an individual is within a predetermined limit, and otherwise the red LED is illuminated. In one embodiment, the alcohol-monitoring device may be included in an automotive vehicle that is readily available, typically disposed so that the individual can conveniently place the tissue on the device. In some cases the device may function as an information guide indicating whether it can only be operated and in other cases the ignition of the automotive rely on determining whether the blood-alcohol level of the individual is lower than the prescribed level It is possible.

3. Contact biometric sensor

The biometric sensor may be configured in a manner similar to that shown in Figures 1 and 3, but the skin region must be set to contact the platen. Such designs have certain additional features that result from the interaction of the platen and light. Sometimes additional information is allowed to be combined as part of spatial spectral data collection.

6, an embodiment for providing a front view of the contact biometric sensor 601 is shown. As with the sensor shown in FIG. 1, the touch sensor 601 has one or more illumination subsystems 621 and a detection subsystem 623. Each illumination subsystem 621 includes one or more white light sources 603 and an illumination lens unit that makes the light provided from the light source 603 into a desired shape. As with non-contact devices, the illumination lens portion can generally include any combination of optical elements and can sometimes include a scanner mechanism. In some cases, the illumination light is provided as polarized light by disposing a polarizer 607 through which the illumination light passes. The example of the white light source 603 and the light source 603, which include the broadband and narrowband light sources described above, may be set to provide light sources having different shapes in different embodiments.

The illumination light passes through the platen 617 and is directed to the illumination lens portion 621 to illuminate the skin portion 119. The sensor arrangement 601 and components can be advantageously selected to minimize direct reflection of the illumination lens section 621. [ In one embodiment, such direct reflectance is reduced by relatively directing the illumination subsystem 621 and the detection subsystem 623 such that the amount of directly reflected light is minimally detected. For example, the optical axis of the illumination subsystem 621 and the detection subsystem 623 may be such that the mirror placed on the platen 617 does not direct a detectable amount of illumination light to the detection subsystem 623 It can be placed at an angle. In addition, the optical axes of the illumination and detection subsystems 621 and 623 can be placed at such an angle that the acceptance of the angles of the two subsystems is less than the critical angle of the system 601, corresponding to the platen 617; Such a setting avoids a perceptible effect on the overall internal reflectance between the platen 617 and the skin region 119.

The presence of the platen 617 does not hinder the ability to reduce the light directly reflected by the use of the polarizer. The detection subsystem 623 may include a polarizer 611 that includes an optical axis that is substantially orthogonal or parallel to the polarizer 607 by the illumination subsystem 621. Surface reflection in the area of contact between the platen 617 and the skin region 119 is less than that of the polarizer < RTI ID = 0.0 > (617) < / RTI > since the light from the sample necessarily experiences sufficient scattering for changes in polarization conditions before it can be detected from the detector 615 611 and 607 are oriented substantially orthogonal to each other. The detection subsystem 623 may additionally engage a detection lens section that forms an image of the region from the vicinity of the platen 617 surface to the detector 615. In one embodiment, the detection lens portion 613 includes a scanning mechanism (not shown) for sequentially relaying a portion of the platen region to the detector 615. In embodiments where the detector 615 is sensitive to infrared rays, such as a Bayer filter arrangement is used, the infrared filter 614 may be included to reduce the amount of infrared detected. Conversely, as depicted above, the infrared filter 614 may be omitted in some embodiments and the additional light source 603 emitting in the infrared may be included in some embodiments.

As with the other devices depicted above, the detection subsystem 623 is typically sensitive to light that passes through the skin surface and undergoes optical diffusion in the skin and / or underlying tissue. Polarizers can sometimes be used to create or emphasize surface features. For example, if the illumination light is polarized in the (P) direction parallel to the platen 617 and the detection subsystem 623 is coupled in the vertical (S) direction to the polarizer 611, It is blocked by the extinction ratio of the pair. However, light that effectively crosses the skin from the peak point, which randomizes the polarization, is optically diffused (even though the skin has its own specific polarization quality, as is known in the art). This acknowledges that some of the absorbed and re-emitted light is observed by the S-polarized imaging system, at a state of 50%.

A side view according to one embodiment of the invention is schematically illustrated in Fig. 7a. Clearly, this figure clearly shows the illumination subsystem 621 without showing the detection subsystem. In this embodiment, the illumination subsystem 621 has a plurality of spatially distributed white light sources 703. As shown in the figure, the illumination lens portion 621 is set to provide floodlighting, but in other embodiments it may be combined with a cylindrical lens portion, a focal lens portion, or other optical configuration known in the art, But may be arranged to provide different patterns of illumination.

The arrangement of the white light source 703 in Fig. 7A need not be an actual plane as shown in the figure. For example, in other embodiments, optical fibers, fiber bundles, or fiber optical faceplates or tapers may be placed in an illuminated plane where light from a light source is reimaged onto the skin region 119 at some convenient location Light can be transmitted. The light source can be controlled by turning on and off the operating current as the LEDs do. Alternatively, if an incandescent light source is used, the switching of light may be accomplished using a micro-precision machining technique ("MEMS") to control the shape of a spatial light modulator such as a liquid crystal adjustor, diaphragm, mirror, Lt; / RTI > Such a configuration can simplify the structure of the sensor. One embodiment showing the use of electrical scanning of optical fibers and light sources such as LEDs is shown in Figure 7B. The individual fibers 716a connect each of the LEDs located in the illumination array 710 to the imaging surface and the other fiber 716b can include the photodiode array, CMOS array, or CCD array And relays it back to the imaging device 712. The set of fibers 716a and 716b thus defines the optical fiber bundle 714 used for the relay light.

Another embodiment of the contact biometric sensor is schematically illustrated in the front view of Fig. In this embodiment, the biometric sensor 801 includes one or more white light illumination subsystems 823 and a detection subsystem 825. The illumination subsystem 823 includes a white light source 803 that provides light passing through the illumination lens portion 805 and the polarizer 807 to direct the skin region 119 to the platen 817, . A portion of the light is scattered distally to the detection subsystem 825, including the imaging lens portions 815 and 819, the crossed polarizers 811, and the dispersive optical component 813, do. The first imaging lens portion 819 parallelizes the light reflected from the skin portion 119 for transmission through the crossed polarizer 811 and the dispersive optical component 813. [ The separated spectral components are focused on the detector 817 separately by the second imaging lens unit 815. [

The contact biometric sensors as shown in Figs. 6 to 8 also depend on the setting of the illuminated area to move relative to the skin area. As noted before, such relative movement is accomplished by a mechanism for scanning the illumination light and / or by moving the skin region. The presence of the platen in the contact-sensor embodiment generally facilitates movement of the skin region by restricting the surface of the skin region in a defined plane; In embodiments where freedom of movement in three dimensions is permissible, additional difficulties may result from movement of the skin region beyond the imaging thickness. The read sensor thus includes a platen that can be transferred to the contact biometric sensor as in the manner generally depicted in FIG. 4, but which prevents movement of the skin region in one direction. In some embodiments, the read sensor may be a fixed system, while the contact setup is followed by a roller system in which the skin portion rolls over the transparent roller structure in white light. Encoders can help to record location information and align the entire two-dimensional image from a sequence of results of image slices, as is well known in the art. The light received from the discontinuous portion of the skin region is used to make an image.

The description of the non-contact and contact biometric sensor is focused on embodiments in which white light is used, while other embodiments may use different spectral combinations of light in similar structure devices. Additionally, other embodiments may include various additional optical conditions to provide a multicolor spectral state. A description of some of such multicolor spectral applications is given in commonly assigned U.S. Patent Application No. 10 / 818,698 entitled "MULTISPECTRAL BIOMETRIC SENSOR ", filed April 5, 2004 by Robert K. Rowe et al .; U.S. Patent No. 11 / 177,817 entitled "LIVENESS SENSOR ", filed on July 8, 2005, by Robert K. Rowe; U.S. Provisional Patent Application No. 60 / 576,364 entitled "MULTISPECTRAL FINGER RECOGNITION" filed on June 1, 2004, Robert K. Rowe and Stephen P. Corcoran; U.S. Provisional Patent Application No. 60 / 600,867 entitled "MULTISPECTRAL IMAGING BIOMETRIC" filed on August 11, 2004, Robert K. Rowe; U.S. Patent No. 11 / 115,100 ("MULTISPECTRAL IMAGING BIOMETRICS" filed on April 25, 2005, Robert K. Rowe); U.S. Patent Application No. 11 / 115,101 entitled "MULTISPECTRAL BIOMETRIC IMAGING" filed on April 25, 2005; U.S. Patent No. 11 / 115,075 entitled "MULTI SPECTRAL LIVENESS DETERMINATION" filed on April 25, 2005; U.S. Provisional Patent Application No. 60 / 659,024 entitled " MULTISPECTRAL IMAGING OF THE FINGER FOR BIOMETRICS "filed March 4, 2005, Robert K. Rowe et al .; U.S. Provisional Patent Application No. 60 / 675,776 entitled "MULTISPECTRAL BIOMETRIC SENSORS" filed on April 27, 2005 by Robert K. Rowe; And US Patent Application No. 11 / 379,945 entitled "MULTISPECTRAL BIOMETRIC SENSORS ", filed April 24, 2006, by Robert K. Rowe. Each of the above-cited patent applications is incorporated herein by reference in its entirety for all purposes.

The non-contact and contact biometric sensors depicted above use white light imaging in certain embodiments. The use of white light allows images to be collected simultaneously in multiple colors, and the overall speed of data acquisition is faster than in embodiments where discontinuous states are collected separately. This reduced data-collection time leads to the reduction of unwanted images as the skin moves during data collection. The overall sensor size can also be reduced and can be provided at a lower cost with the use of a smaller number of light sources compared to the use of discrete light sources of different colors. Corresponding to reduction is also possible in an electric appliance used to support the co-operation of the light source. In addition, a color photographing apparatus is generally available at a generally lower price than a monochromatic photographing apparatus.

The use of white light imaging is also possible to reduce the size of the data when the sensor is designed to use all the pixels to obtain the desired resolution. For example, a typical design standard can provide a 1-inch surface with a resolution of 500 dots per inch. This can be achieved with 500 x 500 pixels of a monochrome camera. It can also be obtained with a 1000 x 1000 color camera when each color plane is extracted separately. The same resolution can be obtained by using a 500x500 color imaging device and conversion to {R, G, B} pairs and extraction of monochromatic portions of the image. This is a particular example of a more general sequence in which a color imaging device is used as the conversion to the primary-tricolor color pair and is performed with the extraction of monochrome portions of the image. Such a process generally allows the desired resolution to be obtained more effectively than with other extraction techniques.

4. Integrated multicolor spectrum / TIR  sensor

In some embodiments, the multicolor spectral imaging enabled by the sensor described above can be integrated with a conventional TIR imaging system. A diagram of the integration showing such a multicolor spectrum-analyzing capability and an integrated bright-face fingerprint sensor is provided in FIG. The sensor includes a light source 953, a platen 961, and an imaging system 955. The imaging system 965 may include a lens, a mirror, an optical filter, a digital imaging arrangement, and other optical elements (not shown). The optical axis of the imaging system is at an angle greater than the critical angle with respect to surface 961a. Light from the light source 953 passes through the platen 961 and illuminates the diffusing reflective coating 963, which extensively illuminates the platen surface 961a. In the absence of the fingers 969, the light experiences a TIR at the surface 961 and some are collected and form a TIR image that is uniformly illuminated by the imaging system 955. When the skin of the appropriate index of refraction is in optical contact with the platen surface 961a, the contact points form a relatively dark area in the resulting image. Such different settings, using different positions for the light source 953 and / or the imaging system 955, may result in a dark-side TIR image. For example, if the platen 961 is illuminated with a light source 957 and imaged by the imaging system 955, a dark-planar image is produced where the contact point is relatively light. In some dark-side embodiments, the coating 963 may comprise an optical absorbing material.

The second imaging system 959 searches through the face 961b at the finger 969. [ The imaging system 959 has an optical axis that is less than the critical angle with respect to surface 961a. In some embodiments, imaging system 959 is oriented generally perpendicular to surface 961a. The imaging system may include a lens, a mirror, an optical filter, and a digital imaging arrangement (not shown). In this manner, when the light source 953 is illuminated, the direct image can be captured by the camera 959, while the TIR image can be captured by the camera 955. [ Even when the TIR image is adversely affected by water, dust, poor contact, dry skin, etc., the image captured by the camera 959 is relatively unaffected and has generally useful biometric features including fingerprint patterns do.

The imaging system 959 may further be coupled with an optical polarizer (not shown), which may be a linear polarizer or an elliptical (e.g., circular) polarizer. Further, another light source 959 may be added to the system. Light source 959 may be an incandescent light source, such as a tungsten-halogen lamp or others commonly known in the art. Light source 957 may be another broadband light source, such as white light LEDs or others known in the art. The light source may be a quasi-monochromatic light source, such as a solid state LED, an organic LED, a laser diode, or any other type of laser or quasicone light source known in the art. Light source 957 may further include a lens, a mirror, an optical diffuser, an optical filter, and other such optical elements.

Light source 957 may be substantially the same or may provide for different illumination wavelengths, angles, and / or polarization conditions. In the example below, one of the light sources 957a may have an optical polarizer (not shown) oriented substantially orthogonally to the polarizer coupled in the imaging system 959. [ Such optical structures tend to emphasize the features of the skin underlying the surface. One of the light sources 957b can couple with a polarizer that is substantially parallel to the polarizer used in the imaging system 959 which tends to emphasize the surface characteristics of the skin. Alternatively, one of the light sources 957b may omit the polarizer and cause random polarization. Such random polarization can be depicted as a combination of polarizations parallel and perpendicular to the polarizer in the imaging system 959, resulting in an image combining features from the two polarization states. The light source 957 may be the same wavelength or different wavelengths (with or without polarization). The number and arrangement of light sources 957 may vary in different embodiments to accommodate configuration-factor limitations, illumination-level limits, and other production requirements.

In one embodiment, light source 957 is oriented at an angle less than the critical angle with respect to surface 961a. In a first embodiment, the light source may be positioned at an angle and position where the direct reflection of the light source is not visible by the imaging system 959 or 955. Such a direct reflection can also be mitigated through the use of a crossed-polarizer setting, but some unwanted images are generally present if the light source is in the field of view. In addition, the parallel and unpolarized settings are very easy to be reflections again.

Attempts to deceive systems can generally be described in three categories: (1) a thin transparent film is placed over a finger or other tissue; (2) use a thin scattering film over a finger or other tissue; And (3) use a thick sample over a finger or other tissue. Embodiments of the present invention have great advantages in the second and third cases, in other words, when the fake includes a thick film or a thin scattered film. Attempts to combine the geometry of different fingerprint patterns can be detected by comparing the traditional pattern with the TIR pattern if the fake comprises a thin and transparent film, i.e., is not substantially absorbed and does not scatter; A more detailed description of how such comparisons may be made is provided in U.S. Patent Application No. 11 / 015,732, hereby incorporated by reference.

Fakes using thin scattered films can also be combined with other topographic patterns in an attempt to deceive traditional sensors, in other words, substantially unabsorbed films with a significant amount of optical scattering. The spectral imaging described here allows the imaged tissue characteristics to be imaged even if the image of the actual finger is obscured. Conversely, a thick sample provides a combination of scattering samples and absorbance characteristics that ensure that the detected light does not at least pass significantly through the adjacent tissue. Attempts to combine topographical maps of different fingerprint patterns to deceive traditional sensors can be detected according to embodiments of the present invention by evaluating the spectra and other optical properties of thick samples and comparing them to actual tissue characteristics.

5. Tissue biometric sensor

Another embodiment of the contact biometric sensor provided in the embodiment of the present invention is a tissue biometric sensor. "Image texture" is generally referred to as part of a large number of metrics that describe certain aspects of the spatial distribution of the hue characteristics of the depicted image. For example, some of these tissues, usually found in fingerprint patterns or grain, are like flow, and can be well described by measurement standards such as orientation and coherence. In organizations with spatial order (at least locally), the power spectrum associated with a particular characteristic of the Fourier transform is important, such as energy compactness, dominant frequency, orientation, and so on. Statistical moments such as a specific mean, variance, skewness, and kurtosis can be used to describe the tissue. Moment invariants, which are combinations of various moments that are invariant to scale, rotation, and other causes, can be used. The spatial dependent metrics of gray tonality can be created and analyzed to describe image organization. The entropy of the image region can be calculated as a measure of image organization. Various types of wavelet transforms can be used to describe the facets of image organization. Other mechanisms, such as steerable pyramids, Gabor filters, and space-bound primitives can be used to describe image organization. These and other measurements of tissues well known in the art may be used either individually or in combination in an embodiment of the present invention.

Image organization may be evidenced by changes in pixel intensities throughout the image that may be used in embodiments of the present invention to perform biometric functions. In some embodiments, additional information can be extracted when such an analysis of the organization is performed for different spectral images extracted from a multicolor spectral data set, resulting in a tissue description of the color of the skin region. These embodiments allow the biometric function to be conveniently performed by reading a portion of the image of the skin area. The tissue properties of the skin are expected to be nearly consistent across the skin area and allow the biometric function to be performed with measurements made at different parts of the image site. In many instances, it is not even required that portions of the skin region used in different measurements overlap each other.

The ability to use different parts of the skin area provides considerable flexibility in the use of structural designs that can be used. This is partly the result of the fact that biometric metric matching can be performed statistically instead of requiring a match to a deterministic spatial pattern. The sensor can be set in a dense manner because it does not need to capture images over a specified spatial area. The ability to provide a small sensor also makes the sensor more economical than a sensor that needs to acquire complete spatial information to perform biometric functions. In another embodiment, the spatial spectral information is used, while the biometric function may be performed in purely spectral information in other embodiments.

An example of the structure of the tissue biometric sensor is schematically shown in Fig. 10A. The sensor 1000 includes a plurality of light sources 1004 and a photographing apparatus 1008. In other embodiments, the light source comprises a quasi-monochromatic light source, while in some embodiments the light source 1004 comprises a white light source. Similarly, the photographing apparatus 1008 may include a monochrome or color photographing apparatus, which is a photographing apparatus having a Bayer pattern as an example. The sensor 1000 is referred to herein as a "contact" sensor because the image is collected and measured substantially in the plane of the skin region 119. It is possible, however, to have some other setting with the imaging device 1008 that is in contact with the skin area 119 when operating the sensor and the imaging device 1008 that is removed from the plane of the skin area 119 Do.

The two illustrated embodiments can be seen in Figures 10b and 10c. In the embodiment of Fig. 10B, the photographing apparatus 1008 substantially contacts the skin region 119. Fig. Light from the light source 1004 propagates under the tissue of the skin region 119 and causes light scattered from the skin region 119 and underlying tissue to be detected by the imaging device 1008. Another embodiment in which the imaging device 1008 is removed from the skin region 119 is schematically shown in Fig. 10C. In this figure, the sensor 1000 'conveys a plurality of optical fibers, which transmit an image to the imaging device in the plane of the skin region 119, and deliver the image pixel of the individual in a full internal reflection along the fiber, And an optical device 1012 that may include an optical device. In this method, the pattern of the light detected by the photographing apparatus 1008 is substantially the same as the pattern of light formed in the plane of the skin region 119. The sensor 1000 'may operate in substantially the same manner as the sensor 1000 illustrated in FIG. 10B. Light from the light source 1004 propagates through the skin region 119 and into the underlying skin tissue where it is reflected and scattered. In such an embodiment, the image formed by the imaging device 1008 is substantially the same as the image formed by the device as in FIG. 10A, since the information is only delivered substantially without loss.

In embodiments where purely spatial information is used to perform the biometric function, the spectral characteristics in the received data are recognized and compared with the registration database of the spectrum. The resulting tissue spectrum of a particular individual includes a combination of unique spectral characteristics and spectral characteristics that can be used to recognize an individual. The device has been directed to extract the associated spectral characteristics. Extraction of related spectral features can be performed with a number of different techniques, including discriminant analysis techniques. When the visual analysis of the spectral output is not readily identifiable, such analytical techniques can iteratively extract the unique features that can be distinguished to perform biometric functions.

An example of a particular technique is the commonly assigned US Patent No. 6,560,352 entitled " APPARATUS AND METHOD OF BIOMETRIC IDENTIFICATION AND VERIFICATION OF INDIVIDUALS USING OPTICAL SPECTROSCOPY "; U.S. Patent No. 6,816,605 entitled " METHODS AND SYSTEMS FOR BIOMETRIC IDENTIFICATION OF INDIVIDUALS USING LINEAR OPTICAL SPECTROSCOPY "; U.S. Patent No. 6,628,809 entitled " APPARATUS AND METHOD FOR IDENTIFICATION OF INDIVIDUALS BY NEAR-INFRARED SPECTROSCOPY "; U.S. Patent Application No. 10 / 660,884 (entitled "APPARATUS AND METHOD FOR IDENTIFICATION OF INDIVIDUAL BY NEAR-INFRARED SPECTROSCOPY" filed on September 12, 2003, Robert K. Rowe et al.); And US Patent Application No. 09 / 874,740 entitled "APPARATUS AND METHOD OF BIOMETRIC DETERMINATION USING SPECIFIED OPTICAL SPECTROSCOPY SYSTEM" filed on June 5, 2001, by Robert K. Rowe et al. Each of the above-cited patent applications is incorporated herein by reference in its entirety for all purposes.

The ability to perform biometric functions with image-tissue information, including biometric identification, can take advantage of the fact that a significant portion of the signal from the living body is capillary. For example, when the skin region 119 includes a finger, the known physiological characteristic is that the capillary blood of the finger follows the pattern of the outer fingerprint peak structure. Therefore, the contrast characteristics of the fingerprint related to the illumination wavelength are related to the spectral characteristics of the blood. In particular, the image contrast obtained at wavelengths longer than about 580 nm is significantly reduced compared to images taken at shorter wavelengths of about 580 nm. Other optical effects, such as fingerprint patterns generated by non-blood pigment and Fresnel reflectance, have different spectral contrasts.

Light scattered from skin region 119 may undergo various other types of relative tissue analysis in other embodiments. Some embodiments utilize the form of moving-window analysis of image data received from the collected light to produce a figure of merit, where the measurements of the tissue or the figure of merit are evaluated. In some embodiments, the moving-window operation may be replaced one block at a time or with a standardized analysis. In some embodiments, one region or whole image of the image may be analyzed at one time.

In one embodiment, a fast-Fourier transform is performed in one or more regions of the image data. The in-band contrast performance index C is generated in such an embodiment as the ratio of the average to the in-band power or the direct current power. Specifically, there is an index i corresponding to one of a plurality of wavelengths included in white light, and the contrast performance index

to be.

In this expression, Fi (?,?) Is the Fourier transform of the image fi (x, y) at the wavelength corresponding to the index i, where x and y are the spatial coordinates of the image. The range defined by Rlow and Rhigh expresses the restriction of the spatial frequency of interest in the fingerprint feature. For example, Rlow may be approximately 1.5 fringe / millimeter in one embodiment and Rhigh may be 3.0 fringe / millimeter. In another expression, the contrast performance index can be defined as the ratio of the integrated power of two different spatial frequency bands. The above equation is a special case in one of the bands including only the DC spatial frequency.

In another embodiment, the moving-window average and the moving-window standard deviation are calculated with the collected body data and used to generate the figure of merit. In this embodiment, for each wavelength corresponding to index i, the moving-window mean [mu] i and the moving-window standard deviation [sigma] i are calculated from the collected image fi (x, y). The moving-window of each calculation can be the same size and can be conveniently selected by concatenating the order of the 2-3 fingerprints. Preferably, the window size is large enough to remove the fingerprint feature, but small enough that the background change can be sustained. In this embodiment, the figure of merit Ci is calculated as the ratio of the moving-window standard deviation to the moving-window average.

In another embodiment, a similar process is performed, except that a moving-window range (i.e., maximum (image value) - minimum (image value)) is used instead of moving-window standard deviation. Thus, similar to the previous embodiment, the moving-window mean [mu] i and the moving-window range [delta] i are calculated from the image fi (x, y) collected for each wavelength corresponding to index i. The window size for the calculation of the moving-window averages is again sufficiently large enough to remove the fingerprint feature, but small enough to keep the background change. In some cases, the window size for the calculation of the moving-window average is equal to the size for the moving-window range calculation. A suitable value is a sequence of 2-3 fingerprint peaks in one embodiment. In this embodiment, the figure of merit is calculated as the ratio of the moving-window average.

This embodiment and the above-described embodiment can be considered as a specific case of a more general embodiment in which the moving-window calculation is performed with the collected data for calculating the moving-window concentrated measurement and the moving-window variation measurement. Certain embodiments illustrate the case where a centralized measurement includes a simple average, but more generally may include other types of statistical centralized measurements, such as a weighted average or median in a particular embodiment. Similarly, certain embodiments illustrate the case where the change measure includes a standard deviation or range, but more generally may include other kinds of statistical change measure, such as a median absolute deviation or a standard error, in a particular embodiment. have.

In other embodiments that do not use explicit moving-window analysis, wavelet analysis may be performed on each of the spectral images. In some embodiments, the wavelet analysis may be performed in such a way that the resulting coefficients are approximately invariant in space. This can be done by performing undecimated wavelet decomposition, applying a double-triple complex wavelet method, or some other kind of method. Gabor filters, steerable pyramids and other types of decomposition can also be applied to produce similar coefficients. Regardless of which decomposition method is selected, the result is a set of coefficients that is proportional to the magnitude of the change corresponding to a particular underlying function at a particular location in the image. To perform fake detection, the wavelet coefficients or other derived summaries can be compared to the coefficients expected from the sample of intrinsics to it. If the comparison shows that the results are fairly close, the sample is considered intrinsic. Otherwise, the sample is judged to be fake. In a similar manner, the coefficient may also be used for biometric verification by comparing a previously recorded set from a person referred to as a person, such as a set of currently measured coefficients.

6. Preferred applications

In various embodiments, the biometric sensor can be operated as a computing system to perform biometric functions, whether it is non-contact, contact, or any type of tissue sensor described above. Figure 11 schematically illustrates how individual system components may be implemented in a separate or integrated manner. The computing device 1100 is shown to be composed of hardware elements that are also electrically connected through the bus 1126, which is also connected to the biometric sensor 1156. The hardware components may include a processor 1102, an input device 1104, an output device 1106, a storage device 1108, a computer readable recording medium reader 1110a, a communication system 1114, A processing accelerator 1116, and a memory 1118. The computer readable recording medium reader 1110a is further coupled to a computer readable recording medium 1110b and the combination can be configured to include a computer program that is collectively and remotely located to include computer readable information temporarily and / , ≪ / RTI > fixed, and / or removable storage devices. The communication system 1114 can include other types of wired, wireless, modem, and / or connection boundaries and allows data to be exchanged with external devices.

The computing device 1100 also includes software elements such as programs designed to implement the method of the present invention as shown to include the computing system 1124 and other code 1122 located within the current working memory 1120 . It will be apparent to those skilled in the art that many changes may be used in response to a particular need. For example, custom-made hardware may also be used and / or special components may be implemented in hardware, software (including portable software such as applets), or both. Also, connections may be used to other computing devices, such as network input / output devices.

As in the example of one embodiment of the present invention, the multicolor spectrum state may comprise a plurality of different wavelengths of illumination light. The tissue measure may be a measure of the image contrast produced at a particular spatial frequency of the image. "Image contrast" is referred to herein as a measure of the change in hue associated with a standard hue value over a region of an image. In the case of a live uncovered fingers imaged using visible wavelengths in a manner similar to that described herein, a significant portion of the fingerprint signal follows the capillary. In part this is due to the physiological characteristics that capillaries in known fingers follow a pattern of external fingerprint peaks. Therefore, the contrast of the fingerprint characteristics related to the illumination wavelength can be expected to be related to the spectral characteristics of the blood. In particular, the contrast of images taken at wavelengths longer than about 580 nm is significantly reduced compared to images taken at wavelengths less than about 580 nm. Other optical effects, such as fingerprint patterns generated by non-blood pigment and Fresnel reflectance, have different spectral contrasts.

The absorbance spectrum of the oxygenated blood in the wavelength range from about 425 nm to about 700 nm is shown in FIG. In an exemplary embodiment, although the present invention does not limit the number of multicolor spectrum states used or the use of any particular wavelength, it can be seen that in this example there are five different wavelengths of 445 nm, 500 nm, 574 nm, 610 nm, and 660 nm This is used to determine the multicolor spectrum state. Each of the wavelengths is identified in the spectrum of FIG. As shown in the figure, the absorbance value of blood is largest at the representative wavelength of 445 nm and 574 nm, smaller at 500 nm, and very small at 610 nm and 660 nm. Thus images taken at real fingertips under the illumination wavelengths of 445 nm and 574 nm can be expected to provide relatively high contrast, images taken at 610 nm and 660 nm wavelengths have relatively low contrast, images taken at 500 nm Can be expected to have an intermediate contrast. It is expected that results from other absorbers such as melanin, changes in scattering per wavelength, and various chromatic aberrations also affect contrast measurements and / or other tissue measurements, but these results may be small or may also be false It is a characteristic of a living human finger related to matter and method.

Various embodiments were tested in a data set using twenty normal-finger images collected over thirteen persons and ten false images collected in a thin silicon fake. An example of an image that can be collected is shown in FIG. 13, where portions (a) - (d) show the results of the actual finger, and portions (e) - (h) show the results of the fake. The "planes" identified with each image correspond to different wavelengths. That is, plane 1 corresponds to 445 nm, plane 2 corresponds to 500 nm, plane 3 corresponds to 574 nm, plane 4 corresponds to 610 nm, and plane 5 corresponds to 660 nm. The cause of the plane 6 can be understood with reference to FIG. Plane 6 corresponds to an image that was collected using TIR illumination but imaged by imaging system 159. The wavelength of the TIR illumination used in this experiment was about 640 nm. A comparison of the images can be made between the actual finger-pseudo-pairs, i.e. between the parts (a) and (e), both of which show the result of the plane [3 2 1]. [3 2 1] In the notation, plane 3 means the measurement of red color value in color drawing, plane 2 means green value, and plane 1 means blue value. Similarly, between parts (b) and (f), both showing the result of plane [5 4 5]; Between parts (c) and (g) both showing the result of plane [5 3 1]; Both between the (d) and (h) parts of the TIR-illumination results; A comparison can be made. The [3 2 1] images of sections (a) and (e) show all of the false contrasts, taken with blue and green illumination, and with a relatively high contrast of true tissue and fingerprint peaks. This is taken under red illumination, the fingerprint peaks of the real finger show relatively low contrast, but the fingerprint peaks of the fake show the relatively high contrast of the images of (b) and (f) [5 4 5] It is the opposite of the result.

Utilizing such a difference is obtained by the method of the present invention, summarized in the flow chart of Fig. One or more tissue measurements are developed at each optical condition, and the result set of tissue measurements is compared to an expected value from the real sample. At block 1404, a sample for a tissue sample provided to enable a biometric function is illuminated under different optical conditions. Examples of other optical conditions include other wavelengths as shown in block 1424, other polarization conditions as shown in block 1428, other optical-interaction angles as shown in block 1432, and the like can do. The scattered light from the sample is collected at block 1408 and used for comparative tissue analysis. Another embodiment utilizes another form of moving-window analysis of a multicolor spectral image stack derived from light collected to produce a figure of merit at block 1412 where the measured values of the tissue or the figure of merit . In some embodiments, the moving-window operation 1412 may be replaced one block at a time or with a standardization analysis. In some embodiments, one region or entire image of the image may be analyzed at a time. The figure shows three examples of contrast indexes that can be used in other embodiments, but as this technique becomes apparent in the art after reading this disclosure, other contrast measurements, as well as other tissue measurements, And is not intended to limit this particular identity recognition.

In one embodiment, a fast-Fourier transform is performed on the multicolor spectral image stack as shown in block 1436. [ The in-band contrast performance index C is generated in such an embodiment as the ratio of the average to the in-band power or the direct current power. In particular, under the optical condition i, the contrast index

to be.

In this expression, Fi (?,?) Is the Fourier transform of the image fi (x, y) taken under illumination condition i when x and y are the spatial coordinates of the image. The range defined by Rlow and Rhigh expresses the restriction of the spatial frequency of interest in the fingerprint feature. For example, Rlow may be approximately 1.5 fringe / millimeter in one embodiment and Rhigh may be 3.0 fringe / millimeter. Embodiments in a multicolor spectrum state can be defined solely by different illumination wavelengths, and each condition i is represented by one of the illumination wavelengths [lambda]. In another expression, the contrast performance index can be defined as the ratio of the integrated power of two different spatial frequency bands. The above equation is a special case in one of the bands including only the DC spatial frequency.

In another embodiment, the moving-window mean and the moving-window standard deviation are calculated for the multicolor spectrum stack and used to generate the figure of merit, as shown in block 1440. [ In this embodiment, for each optical condition i, the moving-window mean [mu] i and the moving-window standard deviation [sigma] i are calculated from the collected image fi (x, y). The moving-window of each calculation can be the same size and can be conveniently selected by concatenating the order of the 2-3 fingerprints. Preferably, the window size is large enough to remove the fingerprint feature, but small enough that the background change can be sustained. In this embodiment, the figure of merit Ci is calculated as the ratio of the moving-window standard deviation to the moving-window average.

In another embodiment, a similar process is performed, except that a moving-window range (i.e., maximum (image value) - minimum (image value)) is used instead of moving-window standard deviation. This generally appears at block 1444. Thus, similar to the previous embodiment, the moving-window mean [mu] i and the moving-window range [delta] i are calculated from the image fi (x, y) collected for each optical condition i. The window size for the calculation of the moving-window averages is again sufficiently large enough to remove the fingerprint feature, but small enough to keep the background change. In some cases, the window size for the calculation of the moving-window average is equal to the size for the moving-window range calculation. A suitable value is a sequence of 2-3 fingerprint peaks in one embodiment. In this embodiment, the figure of merit is calculated as the ratio of the moving-window average.

This embodiment and the above-described embodiment can be considered as a specific case of a more general embodiment in which the moving-window calculation is performed on the multicolor spectrum stack to calculate the moving-window concentrated measurement and the moving-window variation measurement . Certain embodiments illustrate cases in which aggregated measurements include simple averages, but more generally may include other types of statistical intensive measurements, such as weighted averages or median values in certain embodiments. Similarly, certain embodiments illustrate the case where the change measure includes a standard deviation or range, but more generally may include other kinds of statistical change measure, such as a median absolute deviation or a standard error, in a particular embodiment. have.

The result of the moving-window analysis is evaluated at block 1416 to determine whether the sample matches the intact tissue sample. If so, a biometric function, including an in-depth analysis to verify the identity or identity of a person with normal tissue, may be performed at block 1448. If the result is that the sample and the intact tissue sample are inconsistent, then it is confirmed to be fake at block 1420. Classification methods such as linear discrimination, quadratic discriminant analysis, K-point, support vector machines, decision trees, and such methods known in the art can be used to perform identification.

Representative results of each of the above described methods are provided in Figures 15A-B. Figures 15A-15C provide the result that the shape of the measured value is calculated from the moving-window fast Fourier transform; Figures 16a and 16b provide the result that the form of the measurement is calculated from the moving-window average and the moving-window standard deviation; 17A and 17B provide the result that the shape of the measured value is calculated from the moving-window average and the moving-window range.

The results shown in Fig. 15A were collected from real fingers and show the results of the in-band contrast performance index obtained from the moving-window fast Fourier transform of each of the multiple samples. The results of each sample are plotted along the transverse coordinates identifying the illumination planes described above; The abscissa can be considered to show the wavelength dependence even though the number of illumination planes corresponded to the wavelength and rather nonlinearly. The data of the individual sample is drawn as a gray line and the average of the entire sample is shown as a thick black line. Most of the results from the real-finger sample are characteristic and show a significant reduction in contrast at the red wavelength of plane 4-5, as expected according to the absorbance characteristics of the blood shown in Fig. 12, "V" shape is expected in (planes 1-3). The contrast value of plane 6 does not coincide with the other planes depending on the other optical terrain used to collect this image, but the values from this plane provide additional discrimination.

The results of both the real finger and the fake are shown in FIG. 15B. In this case, the result of the real finger is shown connecting the diamond shape with a solid line, and the fake result is shown with a dotted line connecting the circle shape. Fake is a real finger covered with thin film. The fake shows a high contrast under red illumination compared to the expected contrast of the intrinsic sample, as evidenced by the experimental results in Illumination planes 4, 5, and 6. In other cases, the relative comparison of the contrast performance index may be more certain than an absolute determination, such as by evaluating whether the red contrast value is less than a factor a of the blue-green value. Different embodiments may use different values of alpha, such that the expected values are approximately alpha = 0.5, alpha = 0.75, and so forth.

Multidimensional scaling can be used to process data to provide a clear quantitative discrimination between real organization and fake. This is shown in Figure 15C, which shows that the multi-dimensional scaling result is plotted at two coordinates. In this example, the coordinates correspond to the scores of the eigenvectors obtained from principal component analysis ("PCA") of the contrast data; In particular, in this figure, "Factor 1" and "Factor 2" are the data from the first two eigenvectors generated by the Matlab program, available from Mathworks, Inc., headquartered in Natick, Mass. It is a score. The circles are used to indicate the result of the induction of the fake, while the induced results of the real finger are shown as asterisks. The clear division is clear between the two, and the result in Fig. 15C is used as a fractional figure. - The lines drawn on the graph are one possible separation line. Unknown samples analyzed in the same way that produce results on the left side of the separator line can be identified as intrinsic samples in block 1416 of FIG. 14, while the bottom right results of the separator can be identified as fake. Here, while the result is shown as a two-dimensional space with other regions corresponding to other characteristics of the sample, other regions of a certain dimension of space can be used to distinguish the sample, such as by having a hyperplane that more generally segregates have. More generally, as depicted elsewhere in this disclosure, various other classification methods can be used to classify whether a sample is a finger of intrinsic or not.

The results in FIG. 16A are similar to the results in FIG. 15B but are obtained in embodiments using the moving-window average and moving-window standard deviation as described above. While the fake results are displayed by connecting the circles with dashed lines, the results from the real fingers are again displayed by connecting the diamond shape to the solid line. As shown in Fig. 15B, under red illumination, the fake shows higher contrast than the intrinsic sample. A separation diagram using the results of FIG. 16A similar to the view of FIG. 15C is shown in FIG. 16B. In this case, the circle is used to display the result of the pseudo, while the result of the real finger is again marked with an asterisk. The result is again obtained as an eigenvector score, provided by the Matlab program from the PCA, especially using the first two eigenvectors. The dividing line is shown to be distinguished from the real organization by falsely indicating to which part of the two-dimensional space the multidimensional scaling result starts. The general behavior shown in Fig. 16B is similar to that shown in Fig. 15C.

The results shown in Figs. 17A and 17B also correspond to the results of Figs. 15B and 15C or Figs. 16A and 16B. In this case, the results are obtained in an embodiment using the moving-window average and the moving-window range of the multicolor spectrum stack as described above. The fake results, indicated by the solid lines connecting the circles, again show a higher contrast than the true-sample results displayed by connecting the diamond to the solid line in Figure 17a under red illumination. 17B again shows the ability to determine a separation line that separates real-tissue results (asterisks) into spaces of eigenvector scores into regions where they are clearly separated from the pseudo-result (circle). As previously described, such a separating capability causes the unknown result to be classified according to which portion of the multidimensional space in block 1416 of Fig.

Various other methods may also be used in other embodiments for evaluating contrast data, as shown in the figures of Figures 15A, 16A and 17A. For example, a linear discriminant analysis device ("LDA") is used in another such embodiment as a contrast discrimination device. Such an analysis, just a courtesy, can use two types of training. The first kind of contrast curve is created by human tissue and the second kind of contrast curve is created by various fake samples.

While the various examples provided above focus on the use of fingers to provide tissue and the use of different illumination-light wavelengths to provide a multicolor spectrum environment, there is no intention to limit thereto. In other embodiments, other polarization conditions may alternatively or additionally be used to determine the multicolor spectrum state. For example, the comparison may be a mode that may include cross-polarization imaging, parallel-polarization imaging, random-polarization imaging, etc. between two or more polarization conditions. In addition, incident light may have other polarization states, such as by having linearly polarized light, circularly polarized light, elliptically polarized light, and the like. In another example, different illumination angles can be used to provide a multicolor spectrum state. The passing thickness of the light changes in accordance with the function of the illumination angle and, as a result, changes in the image contrast which can be analyzed to distinguish between the real organization and the fake, as described above.

Moreover, the present invention is not limited to the specific figure of merit described above, and other or additional tissue-based figure of merit may alternatively or additionally be used in various embodiments. For example, statistical moments can be used, such as moment invariants to obtain a figure of merit to distinguish the depicted samples, spatial dependencies of gray tones, and the like.

Spectral contrast is a relative measure. A convenient result of this fact is that the described method is expected to be robust across a variety of different types of spectral sensors and in a variety of different environmental conditions.

An overview of additional functionality that may be migrated to computing devices is summarized in the flowchart of FIG. In some embodiments, the target skin area is illuminated with white light as shown in block 1804. [ At block 1808, this causes the biometric sensor to receive light from the target skin site. As depicted above, the received light can be analyzed in many different ways to perform biometric functions. The flow chart shows how a particular combination of analysis can be used to perform biometric functions, although not all steps need be performed. In some other cases, a portion of the step may be performed, additional steps may be performed, and / or the indicated steps may be performed in a different order than indicated.

At block 1812, the alive check can be performed with the received light, verifying that the target skin site is not some kind of fake, usually having a characteristic of living tissue. If a fake is detected, an alert may be issued at block 1864. The type of specific alarm to be issued may depend on the environment in which the biometric sensor is disposed. Voice or visual alarms are sometimes issued near the sensor; In other cases, a quiet alert may be sent to the expense or law enforcement personnel.

The received light scattered from the target skin region may be used to obtain a surface image of the target skin region at block 1820. In the example where the target skin region is the bottom surface of the finger, the surface image includes a representation of the peak of the finger and the pattern of the bone, and is compared to a database of traditional fingerprints in block 1824. Additionally or alternatively, the light received at block 1828 may be used to receive a spatial spectral image. This image may be compared to a spatial spectral database having an image associated with the individual at block 1832. In some cases, the comparison may cause the individual to be recognized at block 1836 as the result of the comparison. It is generally anticipated that the identification of a high degree of reliability will be achieved by using the entire spatial spectrum information to provide a comparison with the spatial spectral image. However, in some applications, some individuals may have greater utility of traditional fingerprint data because their fingerprints are in a large law enforcement fingerprint database, but not in a spatial spectrum database. In such a case, embodiments of the present invention conveniently allow identification to be performed by extraction of a traditional fingerprint image.

Spatial spectral data includes additional information that can be used to provide greater assurance in identity verification, whether identity verification is a comparison with a traditional fingerprint database or a comparison with spatial spectral information. For example, as indicated at block 1840, demographic and / or anthropometric characteristics may be evaluated from received light. When the database input matched with the image at block 1836 includes demographic or anthropometric information, a consistency check may be performed at block 1844. For example, an individual who provided himself could be identified as a white male between the ages of 20 and 35 years from the demographics and anthropometric characteristics evaluated. If the database input that matches the image identifies an individual as a black woman of 68 years, there is a clear contradiction in that an alert is issued at block 1864.

Other information, such as the concentration of the analyte at block 1856, may also be determined from the received light. Different behaviors are sometimes taken depending on the determined analyte level. For example, if the blood-alcohol level exceeds a certain threshold, ignition of the vehicle may be inhibited, or an alert may be issued if the patient's blood-glucose level exceeds a certain threshold. Other physiological factors such as skin dryness can be evaluated in other applications, and sometimes other actions are taken correspondingly.

19 is a similar flow chart showing the application of a tissue biometric sensor. At block 1904, a sensor is used to place the skin region of the individual in contact with the detector. As previously reported, the detector may be relatively small since only a portion of the surface of the finger is placed in contact with the detector; Because of the nature of tissue biometry, changes in certain parts of the surface that are in contact during different measurements are not harmful. The data is collected by illuminating the skin region at block 1908 and receiving light scattered from the skin region by the detector at block 1912.

The flow chart shows that another kind of analysis can be performed. In all cases it is unnecessary to perform each of these analyzes, and rather, it is generally expected that only one kind of analysis will be used in most applications. One category of analysis uses only purely spectral information comparisons, which are generally indicated in block 1916. [ Another category of analysis is to determine the image organization from the spatial-spectral information in the light received in block 1920, as generally indicated in blocks 1920 and 1928, and to determine the image organization and organ biometric information And uses the image organization information. Types of analysis Biometric functions such as recognizing individuals in block 1932 at either or both of them are performed.

Thus, although several embodiments have been described above, it will be appreciated by those skilled in the art that various changes, alternatives, and equivalents may be utilized without departing from the spirit of the invention. Therefore, the above description should not be construed as limiting the scope of the present invention, and the scope of the present invention is defined by the following claims.

Claims (77)

A method for evaluating the intrinsic properties of a sample provided for biometric measurements, Illuminating the sample under a plurality of distinct optical conditions; Receiving light scattered from the sample for each of the plurality of distinct optical conditions; Forming a plurality of images each formed from the received light for each of the plurality of discrete optical conditions; Generating a plurality of texture measures, each generated from each of the plurality of images; And And determining whether the generated plurality of tissue measurements is consistent with the sample being an authentic, open biological tissue. The method of Claim 1, wherein the tissue measure comprises an image-contrast measurement. 2. The method of claim 1, wherein illuminating the sample under the plurality of discrete optical conditions comprises illuminating the sample with light having a plurality of different wavelengths. 2. The method of claim 1, wherein illuminating a sample under the plurality of distinct optical conditions comprises illuminating the sample with light under a plurality of distinct polarization conditions. 2. The method of claim 1, wherein illuminating the sample under the plurality of discrete optical conditions comprises illuminating the sample with light at a plurality of discrete illumination angles. 2. The method of claim 1, wherein generating the plurality of tissue measurements comprises performing a spatial moving-window analysis of each of the plurality of images. . 7. The method of claim 6, wherein each of the plurality of tissue measurements comprises a measure of image contrast in a constant spatial frequency. 7. The method of claim 6, wherein illuminating a sample under the plurality of discrete optical conditions comprises illuminating the sample with light having a plurality of different wavelengths; Wherein determining whether the generated plurality of tissue measurements is consistent with the sample being an authentic, open biotic tissue comprises determining whether the image contrast under red illumination is less than the image contrast under blue illumination Of the sample. 7. The method of claim 6, wherein illuminating a sample under the plurality of discrete optical conditions comprises illuminating the sample with light having a plurality of different wavelengths; Wherein determining whether the generated plurality of tissue measurements is consistent with the sample being an authentic, open biologic tissue comprises determining whether image contrast under red illumination is less than a predetermined value , And the intrinsic property of the sample. 7. The method of claim 6, wherein performing the spatial moving-window analysis comprises calculating a moving-window Fourier transform of the plurality of images. 7. The method of claim 6, wherein performing the spatial moving-window analysis comprises calculating moving-window intensities and moving-window variation measurements of the plurality of images. Way. 12. The method of claim 11, wherein the moving-window centralized measurement comprises a moving-window average and the moving-window variation measurement comprises a moving-window standard deviation. 12. The method of Claim 11, wherein the moving-window centralized measurement comprises a moving-window average and the moving-window variation measurement comprises a moving-window range. The method according to claim 6, Wherein generating the plurality of tissue measurements further comprises applying multi-dimensional scaling to map the plurality of tissue measurements to a point within the multi-dimensional space; Wherein the step of determining whether the generated plurality of tissue measurements is consistent with the sample being an authentic, open biologic tissue comprises determining whether the point is in a predetermined region of the multi-dimensional space ≪ / RTI > 15. The method according to claim 14, wherein the multi-dimensional space is a two-dimensional space. A method for evaluating the authenticity of a sample provided for biometric measurement Illuminating a sample with light having a plurality of different wavelengths; Receiving scattered light from the sample for each of the different wavelengths; Forming a plurality of images each formed from the received light for each of the different wavelengths; Generating a plurality of image contrast measurements each generated from one of the plurality of images by performing a spatial moving-window analysis of one of the plurality of images; And And determining from the plurality of image contrast measurements whether the image contrast under red illumination of the sample is less than the image contrast under blue illumination. 17. The method of claim 16, wherein performing the spatial moving-window analysis comprises calculating a moving-window Fourier transform of one of the plurality of images. 17. The method of claim 16, wherein performing the spatial moving-window analysis comprises calculating moving-window concentrated measurements and moving-window variation measurements of one of the plurality of images. Intention evaluation method. 17. The method of claim 16, wherein determining from the plurality of image contrast measurements that the image contrast under the red illumination of the sample is less than the image contrast under blue illumination, Applying multidimensional scaling to map image contrast; And And determining whether the point exists in a predetermined region of the multi-dimensional space. An apparatus for evaluating the intrinsic properties of a sample provided for biometric measurement, Means for illuminating the sample under a plurality of discrete optical conditions; Means for receiving scattered light from the sample for each of the plurality of discrete optical conditions; Means for forming a plurality of images, each formed from the received light for each of the plurality of distinct optical conditions; Means for generating a plurality of tissue measurements, each generated from each of the plurality of images; And And means for determining whether the generated plurality of tissue measurements is consistent with the sample being an authentic, open biological tissue. 21. The apparatus of claim 20, wherein the means for generating the plurality of tissue measurements comprises means for performing spatial motion-window analysis of each of the plurality of images. 22. The apparatus of claim 21, wherein the means for generating the optical contrast measurement further comprises means for generating multi-dimensional scaling to map a figure of merit to a point within the multi-dimensional space; Wherein the means for determining whether the generated plurality of tissue measurements is consistent with the sample being an authentic, open biologic tissue comprises means for determining whether the point is present in a predefined region of the multidimensional space Wherein the sample is an intrinsic sample. Illuminating the target skin region of the individual in contact with the surface with illumination light; Receiving light scattered from the target skin region; Forming an image from the received light; Generating an image-tissue measurement from the image; And Analyzing the generated image-tissue measurements to perform a biometric function, Wherein the received light is received substantially in a plane including the surface. 24. The method of claim 23, wherein the biometric function comprises an antispoofing function, and wherein analyzing the generated image-tissue measurement value comprises: determining from the generated image- And judging whether or not the tissue includes the tissue. 24. The method of claim 23, wherein the biometric function includes an identity function, and wherein analyzing the generated image-tissue measure comprises determining an identity of the individual from the generated image- And performing a biometric function. 24. The method of claim 23, wherein the biometric function includes a demographic or an anthropometric function, and wherein analyzing the generated image-tissue measure comprises: determining from the generated image- And evaluating the characteristics of the measurement. 24. The apparatus of claim 23, wherein the surface is a surface of an image detector; Wherein the step of receiving light scattered from the target skin part comprises receiving light scattered from the target skin part in the image detector. 25. The method of claim 23, wherein receiving light scattered from the target skin site comprises translating a pattern of light from the plane to an image detector outside the plane without substantial degradation or attenuation of the pattern ; And And receiving the relayed pattern from the image detector. 24. The method according to claim 23, wherein the illuminating light is white light. 30. The apparatus of claim 29, wherein the image comprises a plurality of images corresponding to different wavelengths; Wherein the step of generating the image-tissue measurement comprises performing spatial motion-window analysis of each of the plurality of images. 32. The method of claim 30, wherein performing the spatial moving-window analysis comprises calculating a moving-window Fourier transform on the plurality of images. 32. The method of claim 30, wherein performing the spatial moving-window analysis comprises calculating moving-window concentrated measurements and moving-window variation measurements of the plurality of images. 24. The method according to claim 23, wherein the step of receiving light scattered from the target skin part comprises the step of receiving light scattered from the target skin part in a monochromatic image detector. The method according to claim 23, wherein the step of receiving light scattered from the target skin part comprises the step of receiving light scattered from the target skin part in a color image detector. 24. The method of claim 23, wherein analyzing the generated image-tissue measurements to perform the biometric function comprises: comparing the generated image-tissue measurements with reference image-tissue measurements; Wherein the reference image-tissue measurement is generated from a reference image formed from light scattered from a reference skin site; Wherein the target skin region is substantially different from the reference skin region. 24. The method according to claim 23, further comprising the step of comparing the spectral characteristics of the received light with reference spectral characteristics while performing the biometric function. A surface suitable for contacting an individual's intended skin area; An illumination sub-system for illuminating the target skin area when the target skin area contacts the surface; A detection subsystem for receiving light scattered from the target skin region; And An instruction to form an image from the received light; Generating an image-tissue measurement from the image; And a computing device interfaced with the detection subsystem with an instruction to analyze the generated image-tissue measurement to perform a biometric function, Wherein the scattered light is received substantially in a plane including the surface. 38. The method of claim 37, wherein the biometric function comprises a counterfeiting function; Wherein the command to analyze the generated image-tissue measurement comprises an instruction to determine from the generated image-tissue measurement whether the target skin site includes a living tissue. 38. The method of claim 37, wherein the biometric function comprises an identity function; Wherein the command to analyze the generated image-tissue measurement comprises an instruction to determine the identity of the individual from the generated image-tissue measurement. 38. The method of claim 37, wherein the biometric function comprises a function of demographic or anthropometric measurements; Wherein the command to analyze the generated image-tissue measurement comprises an instruction to evaluate an individual's demographics or an anthropometric characteristic from the generated image-tissue measurement. 38. The apparatus of claim 37, further comprising an image detector, The surface being a surface of the image detector; Wherein the detection subsystem comprises the image detector and receives light scattered from the target skin site in the image detector. 39. The apparatus of claim 37, further comprising: an image detector disposed outside the plane; And And an optical device for relaying a pattern of light from the plane to the image detector without substantial degradation or attenuation of the pattern, Wherein the detection subsystem includes the image detector and receives the relayed pattern on the image detector. The biometric sensor according to claim 37, wherein the illumination subsystem illuminates the target skin region with white light. 44. The apparatus of claim 43, wherein the image comprises a plurality of images corresponding to different wavelengths; Wherein the command to generate the image-tissue measurement comprises an instruction to perform a respective spatial-window analysis of the plurality of images. 45. The biometric sensor of claim 44, wherein the instructions to perform the spatial moving-window analysis include instructions to calculate a moving-window Fourier transform of the plurality of images. 45. The biometric sensor of claim 44, wherein the instructions to perform the spatial moving-window analysis include instructions to calculate a moving-window centralized measurement and a moving-window variation measurement of the plurality of images. 38. The biometric sensor of claim 37, wherein the detection subsystem comprises a monochromatic image detector and receives light scattered from the target skin site in the monochromatic image detector. 38. The biometric sensor of claim 37, wherein the detection subsystem comprises a color image detector, and wherein the color image detector receives the light scattered from the target skin site. 38. The method of claim 37, wherein the instructions for analyzing the generated image-tissue measurements to perform the biometric function include: comparing the generated image-tissue measurements to a reference image-tissue measurement; Wherein the reference image-tissue measure is generated from a reference image formed from scattered light; Wherein the target skin region substantially comprises a different one from the reference skin region. The biometric sensor according to claim 37, wherein the computing device further has an instruction to compare the spectral characteristics of the received light with the reference spectral characteristics while performing the biometric function. A white light illumination subsystem arranged to illuminate a portion of the subject's skin with white light; A detection subsystem arranged to receive light scattered from the target skin part, the detection subsystem including a color imager on which the received light is incident; And A command to acquire images of a plurality of spots of the target skin spatially dispersed from the received light in the color photographing apparatus and an instruction to analyze the plurality of spatially dispersed images to perform a living body measurement function, An arithmetic unit interfaced to the detection subsystem, Wherein the plurality of spatially dispersed images correspond to different volumes of the illuminated tissue of the individual. 52. The method of claim 51, wherein the biometric function includes a function to prevent spurious fraud, and the command to analyze the spatially dispersed images includes an instruction to determine whether the target skin site includes a living tissue A biometric sensor. 52. The computer-readable medium of claim 51, wherein the instructions for analyzing the spatially distributed plurality of images to perform the biometric function comprise instructions for analyzing a plurality of the spatially dispersed images Wherein the bio-metrology sensor comprises: 52. The method of claim 51, wherein the command to analyze the plurality of spatially dispersed images to perform the biometric function comprises analyzing the spatially dispersed plurality of images to determine the concentration of the analyte in the blood of the individual Wherein the biometric sensor includes a command to prompt the user. 52. The biometric sensor of claim 51, further comprising a platen in contact with the target skin region, wherein the white light illumination subsystem is adapted to illuminate the desired skin area through the platen. 53. The biometric sensor of claim 51, wherein the white light illumination subsystem is adapted to illuminate the target skin site when the target skin site is not in physical contact with the biometric sensor. 52. The biometric sensor of claim 51, wherein the white light illumination subsystem comprises a broadband white light source. 52. The biometric sensor of claim 51, wherein the white light illumination subsystem includes a plurality of narrowband light sources and an optical device for combining light provided by the plurality of narrowband light sources. The biometric sensor according to claim 58, wherein the plurality of narrowband light sources provide light of a wavelength corresponding to each of the primary color sets. 52. The apparatus of claim 51, wherein the illumination subsystem comprises a first polarizer for polarizing the white light; The detection subsystem includes a second polarizer arranged to face the received light; Wherein the first polarizer and the second polarizer intersect with each other. The biometric sensor according to claim 51, wherein the detection system includes an infrared filter arranged to face the received light before the received light enters the color photographing apparatus. 52. The method of claim 51, wherein the target skin portion is a bottom surface of a finger or a hand; Wherein the biometric function comprises biometric identification; Wherein the command to analyze the spatially distributed plurality of images comprises: Acquiring a surface fingerprint or a palmprint image of the target skin region from the plurality of spatially dispersed images; And And comparing the surface fingerprint or the long fingerprint image with a database of fingerprint or long fingerprint images to verify the identity of the individual. 52. The method of claim 51, wherein the biometric function comprises biometric identification, Wherein the command to analyze a plurality of spatially dispersed images comprises an instruction to compare a database of multiple spatially dispersed images and a multicolor spectral image to identify the identity of the individual. 52. The apparatus of claim 51, wherein the illumination subsystem is adapted to illuminate the target skin site in an illumination area, Wherein the target skin region and the illuminated region move relative to each other. Illuminating a target skin region of an individual with white light; Receiving light scattered from the target skin region by a color photographing apparatus in which light to be received is incident; Acquiring a plurality of spatially dispersed images of the target skin tissue from the received light in the color photographing apparatus; And Analyzing the spatially dispersed plurality of images to perform a biometric function, Wherein the plurality of spatially dispersed images correspond to different volumes of the illuminated tissue of the individual. 65. The method of claim 65, wherein the bio-metering function includes a function of blocking a spoof, and the step of analyzing the spatially dispersed images includes determining whether the target skin region includes a living tissue And performing the biometric function. 66. The method of claim 65, wherein analyzing the spatially dispersed plurality of images comprises analyzing the spatially dispersed plurality of images to assess a demographic or anthropometric characteristic of the individual. How to perform the measurement function. 65. The method of claim 65, wherein analyzing the spatially dispersed plurality of images to perform the biometric function comprises analyzing the spatially dispersed plurality of images to determine the concentration of the analyte in the blood of the individual And performing a biometric function. 65. The method of claim 65, wherein illuminating the target skin region comprises directing the white light through a platen that contacts the target skin region. 65. The method of claim 65, wherein illuminating the target skin region of the individual with the white light comprises illuminating the target skin region of the individual with a broadband white light source. 66. The method of claim 65, wherein illuminating the target skin portion of the individual with the white light comprises: Generating a plurality of narrowband light beams with a plurality of narrowband light sources; And And combining the plurality of narrowband light beams. 72. The method of claim 71, wherein the plurality of narrowband rays have a wavelength corresponding to a set of primary colors. 65. The method of claim 65, wherein illuminating the target skin region comprises polarizing the white light with a first polarized light; Wherein the step of receiving light scattered from the target skin part comprises polarizing the light that is received by the second polarized light, Wherein the first polarized light and the second polarized light are substantially mutually intersected. 65. The method according to claim 65, wherein the step of receiving light scattered from the target skin part includes filtering the received light at an infrared wavelength before the received light enters the color photographing apparatus Way. 66. The method of claim 65, wherein the target skin portion is a bottom surface of a finger or a hand; Wherein the biometric function comprises biometric identification; Wherein analyzing the spatially distributed plurality of images comprises: Acquiring a surface fingerprint or a long-range image of the target skin region from a plurality of spatially dispersed images; And And comparing the surface fingerprint or the long-distance image with a database of the fingerprint or long-distance image to confirm the identity of the individual. 65. The method of claim 65, wherein the biometric function includes biometric identification; Wherein analyzing the plurality of spatially dispersed images comprises comparing the plurality of spatially dispersed images with a database of multicolor spectral images to identify the identity of the individual. 66. The method of claim 65, wherein illuminating the target skin portion of the individual with white light is performed in an illumination area; Wherein the target skin region and the illuminated region move relative to each other.

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