WO2015058460A1 - 一种生物特征成像的方法与设备 - Google Patents
一种生物特征成像的方法与设备 Download PDFInfo
- Publication number
- WO2015058460A1 WO2015058460A1 PCT/CN2014/000330 CN2014000330W WO2015058460A1 WO 2015058460 A1 WO2015058460 A1 WO 2015058460A1 CN 2014000330 W CN2014000330 W CN 2014000330W WO 2015058460 A1 WO2015058460 A1 WO 2015058460A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- optical lens
- image
- lens component
- biometric
- optical
- Prior art date
Links
- 238000003384 imaging method Methods 0.000 title claims abstract description 123
- 230000003287 optical effect Effects 0.000 claims abstract description 204
- 210000000554 iris Anatomy 0.000 claims description 52
- 238000000034 method Methods 0.000 claims description 26
- 239000007788 liquid Substances 0.000 claims description 23
- 210000001747 pupil Anatomy 0.000 claims description 22
- 230000008859 change Effects 0.000 claims description 13
- 238000005286 illumination Methods 0.000 claims description 13
- 230000000704 physical effect Effects 0.000 claims description 13
- 230000000694 effects Effects 0.000 claims description 10
- 238000001228 spectrum Methods 0.000 claims description 4
- 210000003462 vein Anatomy 0.000 claims description 3
- 210000001525 retina Anatomy 0.000 claims description 2
- 238000004590 computer program Methods 0.000 claims 1
- 238000012634 optical imaging Methods 0.000 abstract description 13
- 230000003068 static effect Effects 0.000 abstract 2
- 230000006870 function Effects 0.000 description 12
- 238000012545 processing Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 9
- 238000004458 analytical method Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 7
- 238000012546 transfer Methods 0.000 description 7
- 239000004065 semiconductor Substances 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 4
- 238000013459 approach Methods 0.000 description 4
- 238000006073 displacement reaction Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 239000011521 glass Substances 0.000 description 4
- 229910052710 silicon Inorganic materials 0.000 description 4
- 239000010703 silicon Substances 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000005672 electromagnetic field Effects 0.000 description 2
- 230000003090 exacerbative effect Effects 0.000 description 2
- 238000010191 image analysis Methods 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 238000001459 lithography Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 229910044991 metal oxide Inorganic materials 0.000 description 2
- 150000004706 metal oxides Chemical class 0.000 description 2
- 238000013021 overheating Methods 0.000 description 2
- 238000012885 constant function Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 210000002747 omentum Anatomy 0.000 description 1
- 230000005693 optoelectronics Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000013441 quality evaluation Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/19—Sensors therefor
-
- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B7/00—Mountings, adjusting means, or light-tight connections, for optical elements
- G02B7/28—Systems for automatic generation of focusing signals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
- H04N23/11—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/67—Focus control based on electronic image sensor signals
- H04N23/673—Focus control based on electronic image sensor signals based on contrast or high frequency components of image signals, e.g. hill climbing method
-
- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B3/00—Simple or compound lenses
- G02B3/12—Fluid-filled or evacuated lenses
- G02B3/14—Fluid-filled or evacuated lenses of variable focal length
Definitions
- the present invention relates to the field of optical technology, and more particularly to a technique for imaging biological features. Background technique
- Iris recognition is an emerging biometric technology that is expanding in the field of identity recognition. Secure and convenient identification is a difficult point to develop for mobile terminal business services. Currently, the use of mobile terminals as a means of identity verification mainly relies on passwords and cards, and is difficult to remember, easy to steal, and low in security. Among many identification technologies, iris recognition has the highest security and accuracy, and has the advantages of being unique, not requiring memory, being able to be stolen, and having a high level of security.
- the iris imaging design generally adopts a fixed focus design, and the user needs to actively cooperate to find a suitable iris imaging position, which requires additional hardware devices such as a distance measuring sensor, a tri-color indicator, etc.; and some iris imaging systems.
- the stepper motor or the DC motor is used to drive the front and back movement of the lens to realize iris autofocus and imaging, but the distance measuring sensor is still needed to measure the distance, and the stepping motor or the DC motor is large in volume and large in power consumption.
- a biometric imaging apparatus comprising:
- An optical lens component for optically imaging a biometric of a region of interest; an image sensor for converting an optical image containing the biometric into an electronic image;
- a micro motor controller configured to acquire image quality information of the electronic image, and control the micro motor to adjust the optical lens component according to image quality information of the electronic image to implement Autofocus control is performed on the biometrics of the region of interest.
- a mobile terminal wherein the mobile terminal comprises a biometric imaging device as described above.
- biometric imaging method wherein the method comprises the steps of:
- the micromotor is controlled to adjust the optical lens component to effect autofocus control of the biometric of the region of interest.
- the present disclosure is capable of performing autofocus control on the biometric based on the image quality information of the electronic image of the biometric, avoiding the autofocusing conventionally by measuring the physical distance between the imaging device and the subject, This eliminates the need to configure the hardware required for ranging, such as ranging sensors.
- the present disclosure employs a micro motor to replace the stepper motor or the DC motor to adjust the optical lens component.
- FIG. 1 shows a schematic diagram of a biometric imaging device in accordance with an aspect of the present disclosure
- FIG. 2 shows a schematic diagram of a biometric imaging device in accordance with another aspect of the present disclosure
- FIG. 3 illustrates a flow chart of a biometric imaging method in accordance with an aspect of the present disclosure
- 4 shows a schematic view of a voice coil motor in accordance with an embodiment of the present disclosure
- FIG. 5 shows a schematic diagram of a microelectromechanical system actuator in accordance with an embodiment of the present disclosure
- FIG. 6 illustrates a schematic diagram of binocular segmentation positioned as two separate monocular iris images for left and right eye, in accordance with an embodiment of the present disclosure.
- FIG. 1 shows a schematic diagram of a biometric imaging device in accordance with an aspect of the present disclosure.
- the biometric image forming apparatus 100 includes an optical lens unit 1 10, an image sensor 120, a micro motor 140, and a micro motor controller 130.
- the optical lens component 1 10 is used for optical imaging of the biometric 12 of the region of interest 13.
- the optical lens component 1 10 can be an optical lens assembly that is now imaged with biometric information of a fixed imaging focal plane.
- the material of the optical lens unit can be a combination of an all-glass lens, an all-plastic lens, a combination of glass and plastic lenses, or a liquid lens.
- the iris is described as an example of a biological feature, but it will be understood by those skilled in the art that the biological features also include a retina, an eye, a lip, a face, a vein, and the like.
- the region of interest 13 refers to an area in which the optical lens component is imaged to maintain a sharply focused area, i.e., the optical lens component is capable of clearly imaging the biological features located in the region of interest.
- the size of the region of interest 13 is determined by the depth of field of the optical lens component, which is the difference between the closest and farthest distances that the imaging system can maintain sharply focused. It determines the degree of redundancy in which the user can be from the biometric imaging device, or the range of use of biometric recognition.
- the optical imaging principle is a well-known technique in the art, and for brevity, it will not be repeated here.
- the image sensor 120 is for converting an optical image of a biometric acquired from the optical lens component 110 into an electronic image.
- the image sensor 120 may include photosensitive elements such as a charge coupled device (CCD) and a metal oxide semiconductor device (CMOS), and converts optical imaging of the biometric into an electrical signal using the photosensitive element to obtain a corresponding electronic image.
- the electronic image includes a still image and a dynamic image format
- the dynamic image is a still image stream, also referred to as a video format, that is combined in a chronological order by a plurality of frames of still images.
- Electronic images can be stored in a predetermined image format including, but not limited to, BMP, JPEG, TIFF, RAW, GIF, and PNG.
- the information of the electronic image can also be stored in the cache or in memory in the form of binary digits. For example, each image pixel is represented by 8-bit, 10-bit, 12-bit, or 24-bit binary information, and this information is used as a subsequent biological image.
- Basic processing information such as analysis, identification, etc.
- the micro motor controller 130 is configured to acquire, transfer, or analyze image (or video) quality feature information of electronic images (including still images and moving images) converted by the image sensor 120, and then, according to the image and video quality of the electronic image.
- the information analyzes the biometric or sharpness of the image in real time and utilizes the micromotor 140 to adjust the imaging component characteristics of the optical lens component 110 to effect autofocus control of the biometrics of the region of interest.
- micromotor controller 130 may, for example, acquire an electronic image from image sensor 120 and evaluate the electronic image to obtain image quality characteristic information of the electronic image, such as sharpness, or biometrics of the image.
- image quality characteristic information of the electronic image such as sharpness, or biometrics of the image.
- the electronic image may be evaluated as a whole to obtain the overall image quality information of the electronic image; or the biometric (eg, iris) image contained in the electronic image may be first recognized, and then the image is evaluated.
- the biometric image obtains image quality information of the biometric and uses it as image quality information of the electronic image.
- the image quality information includes, but is not limited to, image sharpness, contrast, average gray scale, image information entropy, pupil spacing, pupil diameter, iris diameter, horizontal corner width, and the like.
- micro-controller controller 130 can quickly locate a biometric region of interest, such as the iris region of the human eye. Taking the iris as an example, the micro-motor controller 130 can simultaneously image the binocular regions of the person. For each image acquired by the image, an image processing algorithm is used to calculate the pupil center position of the left and right eyes in real time, thereby realizing the whole frame. The real-time search and real-time positioning of the binocular iris on the image is performed, and the imaged image is cropped into a single-eye iris image of the left eye or the right eye. As shown in FIG. 6, the image resolution is generally 640 x 480.
- the monocular iris image of the left and right eyes thus obtained by the image segmentation can be used as an analysis object for the image sharpness evaluation of the biometric imaging device 100.
- the image quality function ImageQualityMetncs is imaged for any single or binocular iris.
- the calculation of this function can be implemented by various energy transfer functions F, including but not limited to discrete cosine transform (DCT), fast Fourier transform (FFT). ) or wavelet transform (Wavelet) and so on.
- the calculated image quality information may be a set of image quality arrays, or a single image quality parameter, including but not limited to image sharpness, contrast, average gray scale, image information entropy, pupil spacing, pupil diameter, iris diameter Wait.
- the micro motor controller 130 may also transmit an electronic image to a third party image quality evaluation device (such as a computer, processor, server, etc. not shown) that receives the electronic image and The evaluation is performed to obtain image quality information, and then the image shield amount information is fed back to the micro motor controller 130.
- a third party image quality evaluation device such as a computer, processor, server, etc. not shown
- the micro motor controller 130 may, for example, analyze the image quality information of the electronic image and the image biometric information, and thereby control the micromotor 140 to move the optical lens component 1 10 or the optical lens component. 1 10 The position of the optical lens, or the optical characteristics of the optical lens component 110, such as the optical radius of curvature.
- the above process is repeated a plurality of times to achieve autofocusing of the biometrics of the region of interest. The specific implementation process will be described in detail below.
- the micromotor 140 is used to adjust the position of the optical lens component 110, such as the optical lens in the optical lens component 110 or the optical lens component 110, or to change the optical lens component, for example, by changing the shape of the optical lens in the optical lens component 110.
- the micromotor 140 may be a voice coil motor (VCM) as shown in Fig. 4, which is a device for converting electrical energy into mechanical energy.
- VCM voice coil motor
- the operation of the VCM includes a current passing through an electromagnetic (coil). This will create an electromagnetic field that repels the permanent magnets, thereby enabling vertical movement of the optical lens holder to move the optical lens away from the image sensor.
- the restoring force provided by the spring by the VCM causes the optical lens to approach the image sensor; while the rest of the optical lens is positioned infinity.
- VCM becomes an obstacle to achieve this. Specifically, to make the VCM smaller, smaller coils, magnets and springs are needed. Since the magnetic force is proportional to the volume, smaller coils and magnets require more current to generate enough actuation force, which can make the problem of power consumption and overheating of the mobile terminal more serious. In addition, smaller springs are more fragile, exacerbating stroke lag, lens tilt, and reliability issues. Because VCM suffers from stroke lag, it will slow the autofocus imaging process for biometric regions of interest (such as the iris), such problems in video capture. It became especially prominent. In addition, the high power consumption of the VCM will quickly drain the battery and the heat generated will also degrade the optical performance and imaging quality of the biometric imaging device.
- the motor 140 can also adopt a MEMS Actuators as shown in FIG. 5, the structure of which includes a silicon wafer-based MEMS actuator (movable by a vertical movement)
- the outer casing structural component, the spring that provides the stress relief and the electrostatic comb drive that controls the structural components of the outer casing are manufactured using a semiconductor process with mechanical and electrical properties.
- the comb drive is a pair of electrically conductive structures that create an attractive force that causes the comb drives to be pulled together when a DC voltage is applied.
- the silicon MEMS autofocus actuator can control any of the optical lens groups. The position of one or more lenses moves, while the other lenses can be held in their optimal position to remain stationary, enabling efficient autofocus.
- MEMS actuators can combine the three components (coils, magnets and springs) required in the VCM into a single component, solving the complex physical connection between the three components of the VCM. Smaller, reducing the effects of physical inertia between them, enabling faster focusing, 2-4 times faster than normal VC:M focusing. At the same time, it is manufactured by a semiconductor process, especially lithography, so that power consumption can be controlled to be smaller.
- the biometric imaging device of the present disclosure avoids autofocusing by conventionally measuring the physical distance between the imaging device and the subject, thereby There is no need to configure the hardware required for ranging, such as ranging sensors.
- the biometric imaging device uses a micro motor to replace the stepper motor or the DC motor to adjust the optical lens component.
- the various devices of the biometric imaging device 100 are continuously operated. Specifically, the optical lens component 1 10 optically images the biological features of the region of interest; subsequently, the image sensor 120 converts the optical image of the biometric into an electronic image; then, the micromotor controller 130 acquires the image quality of the electronic image Information, and analysis of the optical lens component based on image quality information analysis of the electronic image.
- continuous means that each device performs optical imaging of the biological features of the region of interest according to the set or real-time adjusted working mode requirements, converts the optical image into an electronic image, and according to Image quality information analysis of electronic images adjusts optical lens section Pieces until the desired focus on the biometric is achieved.
- the micromotor controller 130 obtains the step size of the moving optical lens component 1 10 based on the image quality information of the electronic image, and adjusts the position of the optical lens component 1 10 in accordance with the step size to move the optical lens component 1 10
- the fixed imaging focal plane is used for autofocus.
- the step size here includes the direction in which the optical lens component 1 10 moves (e.g., forward or backward toward the biometric direction) and the distance.
- the micro motor controller 130 compares the image quality information with an empirical lookup table of the entire optical imaging system (ie, the optical lens component 1 10 ), and obtains the current optical according to the image.
- the displacement state of the imaging system so that the number of displacements required to achieve a clear focus imaging state, ie, step, length, is obtained by a lookup table.
- the micromotor controller 130 then controls and rapidly adjusts the position of the imaging focal plane of the optical lens component in accordance with the step size to effect autofocus control of the biometrics of the region of interest.
- the micro motor controller 130 may first control and adjust the position of the imaging focal plane of the optical lens component in a predetermined step to obtain another The electronic image is framed, and the image quality information of the electronic image of the other frame is obtained in the same manner as before.
- the micro motor controller 130 compares the image quality information of the two frames of the previous and second frames, and if the adjusted frame image quality is improved compared to the frame image quality before the adjustment, the micro motor controller 130 focuses correctly and continues to exceed this.
- the direction moves by a predetermined step size, otherwise it moves in the opposite direction, and is repeated a plurality of times until image quality information that satisfies the requirements is obtained.
- the space of the moving optical lens part 1 10 and the optical lens part 1 10 itself will become smaller. In this case, it becomes more difficult to achieve autofocus by moving the optical lens in the optical lens component or the optical lens component.
- the optical lens component 110 in the biometric imaging device 100 is implemented with a liquid lens, and its micro motor controller 130 drives the micro motor 140 according to image quality information of the electronic image to change the The shape of the liquid lens, thereby adjusting the optical characteristics of the optical lens component 1 10, such as the optical radius of curvature, to achieve autofocus.
- the micro motor controller 130 compares the image quality information with an empirical lookup table of the entire optical imaging system (ie, the optical lens component 1 10 ), and obtains the current optical according to the image.
- the optical curvature state of the imaging system resulting in a change in the clear focus imaging state achieved by a lookup table Optical radius of curvature.
- the micromotor controller 130 drives the micromotor 140 according to the optical radius of curvature to change the shape of the liquid lens, thereby causing the optical lens component 110 to have the corresponding optical characteristics.
- the force required to change the shape of the optical lens to adjust its optical characteristics is much less than the force required to move the position of the optical lens, which will save power consumption of the micro-motor.
- device power consumption is an important metric to measure applicability, while low-power biometric imaging devices will meet this requirement, making them suitable for use as a portable device alone or integrated into other portable devices, such as smart Telephone, etc.
- the micro motor controller 130 may determine a specific physical attribute of the biometric having a relatively objective constant value from the electronic image, and obtain an attribute value of the specific physical attribute in the electronic image as the electronic The image quality information of the image is then adjusted according to the attribute value to effect autofocus control of the biometrics of the region of interest.
- the micro motor controller 130 may first locate the biometric in the electronic image by using the aforementioned image analysis algorithm, and query the biometric-specific attribute list for a relatively objective constant value corresponding to the biometric according to the biometric feature.
- a relatively objective constant value means that the value of a particular physical property of a biological feature varies little in the objective world, and does not vary greatly depending on the host of the biological feature.
- the biometric in the electronic image is a human binocular iris (ie, the human eye is included in the electronic image)
- the specific attribute corresponding to the binocular iris can be queried to obtain the pupil spacing (as shown in FIG. 1), because the normal person The pupil spacing varies little and can be considered constant.
- the micromotor controller 130 can calculate the property values of the particular physical property in the electronic image. For example, the micro motor controller 130 can calculate the pixel distance value of the pupil distance of the person in the electronic image / .
- the micro motor controller 130 may obtain an attribute value of a specific physical attribute in the electronic image based on the calculation, such as a pixel distance value of the pupil distance/, and calculate a object distance between the biometric of the region of interest 13 and the biometric imaging device 100.
- Z such as the distance from the human iris plane 12 to the optical lens component 1 10 or the image sensor 120.
- the optical characteristic parameters of the optical lens component 1 10 are known, the optical field of view angle 1 1 is known, and the pupil spacing is substantially constant, and the variation thereof affects the calculation of the object distance D.
- the pixel distance value of the pupil spacing can be regarded as an inverse relationship, that is, the pixel distance value of the human pupil distance calculated by the analysis/7' is larger, the distance of the human eye from the imaging device 100 is smaller (near); The smaller the pixel distance value of the pupil spacing, the human eye away from the imaging device
- the distance of 100 is about (far); therefore, the object distance D can be calculated by the transfer function as described above.
- the micromotor controller 130 can compare the object distance D obtained by the calculation with the current imaging focal length d of the optical lens component 110 to purposefully adjust the optical lens component 110 to achieve autofocus.
- the focus vector is thus the step size of the moving optical lens unit 1 10 .
- the micro motor controller 130 can drive the micromotor to move the optical lens component 110 to a specified position in accordance with the step length L to complete the autofocus.
- the micro motor controller 130 may adjust the optical curvature radius of the liquid lens by driving the micro motor 140 to change the shape of the liquid lens to make a change
- the rear optical lens component 1 10 has a new imaging focal length d that approaches the object distance, thereby completing autofocus.
- the biometric imaging device 100 may further include one or more illumination components 150 for illuminating the region of interest when optically imaging the biometrics in the region of interest to enhance Capture the brightness of the image.
- the illumination component 150 can be, for example, a light emitting diode (LED) or other type of illumination device, and the illumination component 150 can be illuminated with visible or near-infrared light.
- the position of the illumination member 150 on the biometric image forming apparatus 100 may be equally spaced from the optical lens unit 1 10 or may be arbitrarily placed around the optical lens unit 1 10 at an arbitrary pitch.
- the center spectrum of the light emitted by the illumination component 150 can be set according to the particular biometric to be imaged. For example, if the biometric is an iris, the center of the near-infrared light is used.
- the light language range includes 700 nm to 950 nm.
- the biometric imaging device 100 includes three LED lamps that emit near-infrared light, and the center spectrum of the near-infrared light emitted by each of the LED lamps is 780 nm and 850 nm and 940 nm, respectively, so as to better perform different irises of different human races. Imaging illumination.
- the biometric imaging device 100 can image a single-eye iris or simultaneously image the binocular iris.
- the optical resolution of the optical lens component 1 10 in the horizontal direction of the eye needs to be 640 pixels or more, and the optical resolution in the vertical direction should be 480 pixels or more. Accordingly, the image resolution of image sensor 120 needs to be greater than or equal to the optical resolution of the optical lens component.
- the optical resolution of the optical lens component 1 10 in the horizontal direction of the eyes should be 1500 pixels or more, and the optical resolution in the vertical direction should be 480 pixels or more. Thereby ensuring the optical resolution of each monocular image. Accordingly, the image resolution of image sensor 120 needs to be greater than or equal to the optical resolution of the optical lens component.
- the biometric imaging apparatus 100 further includes a filter (not shown) positioned between the biometric to be imaged and the optical lens component to filter the light entering the optical lens component 110 from the biometric feature, thereby enabling reduction The influence of the external environment on the imaging of biometrics, especially the outdoor environment of sunlight, stray light, lighting and dark environments.
- a filter not shown
- FIG. 3 shows a flow chart of a biometric imaging method in accordance with an aspect of the present disclosure. The processing of the biometric imaging method will now be described with reference to Figs. 1 and 3.
- the biometric imaging device 100 acquires an image of the biometric of the region of interest captured by the optical lens component.
- the biometric imaging device 100 can optically image the biological features of the region of interest using optical lens components, such as optical lens sets.
- the material of the optical lens unit can be a combination of an all-glass lens, an all-plastic lens, a combination of glass and plastic lenses, or a liquid lens.
- the iris is described as an example of a biological feature, but it will be understood by those skilled in the art that the biological features include seeing omentum, eye lines, lip lines, face and veins, and the like.
- the region of interest refers to the area where imaging can maintain a clear focus
- the domain, ie, the biometric imaging device 100 is capable of clearly imaging the biological features located in the region of interest.
- the subject may be illuminated with visible or near-infrared light to achieve higher optical imaging quality.
- the biometric imaging device 100 can convert the optical imaging of the biometric into an electronic signal using a photosensitive element such as a charge coupled device (CCD) and a metal oxide semiconductor device (CMOS) to obtain a corresponding electronic image, which is Get an image of the biometric.
- a photosensitive element such as a charge coupled device (CCD) and a metal oxide semiconductor device (CMOS)
- CMOS metal oxide semiconductor device
- the electronic image includes a still image and a dynamic image format
- the dynamic image is a still image stream, also referred to as a video format, which is grouped together in a chronological order by a plurality of frames of still images.
- Electronic images can be stored in a predetermined image format, including but not limited to BMP, JPEG, TIFF, RAW, GIF, and PNG.
- the information of the electronic image can also be stored in the cache or in memory in the form of binary digits.
- each image pixel is represented by 8-bit, 10-bit, 12-bit, or 24-bit binary information, and the information is used as a subsequent biological image.
- Basic processing information such as analysis, identification, etc.
- the biometric imaging apparatus 100 acquires image (or video) quality information of images (including still images and moving images) of the biometrics acquired in step 310.
- the biometric imaging apparatus 100 may evaluate the entire electronic image to obtain overall image quality information of the electronic image; or firstly identify a biometric (eg, iris) image included in the electronic image, and then evaluate the biometric
- the image obtains image quality information of the biometric and uses it as image quality information of the electronic image.
- the image quality information includes, but is not limited to, sharpness, contrast, average grayscale, image information entropy, and the like of the image.
- the biometric imaging device 100 can quickly locate the biometric region of interest, such as the iris region of the human eye. Taking the iris as an example, the biometric imaging device 100 can simultaneously image both eyes of a person, the needle For the image acquired in each frame, the image processing algorithm is used to calculate the pupil center position of the left and right eyes in real time, so as to realize the real-time search and real-time positioning of the binocular iris on the whole image, and cut the image to the left.
- the monocular iris image of the eye or right eye, as shown in Figure 6, has an image resolution of typically 640 X 480.
- the iris image of the left and right eyes obtained by the image segmentation can be used as an analysis object for the image sharpness evaluation of the biometric imaging device 100.
- the image quality function ImageQualityMetrics is imaged for any one or both eyes of the iris.
- the calculation of the function can be implemented by various energy transfer functions, including but not limited to discrete cosine transform (DCT), fast Fourier transform (FFT).
- the image quality calculated by Wavelet transform (Wavelet) or the like may be a set of image quality arrays, or a single image quality parameter, including but not limited to image sharpness, contrast, average gray scale, image information entropy, pupil spacing Wait.
- the biometric imaging device 100 adjusts the optical lens component characteristics based on the image (or video) quality information of the electronic image and utilizes the micromotor device to effect autofocus control of the biometrics of the region of interest.
- the biometric imaging device 100 can analyze the image quality information of the electronic image, for example, and drive the micromotor to generate electromagnetic force to move the position of the optical lens component or change the optical lens component.
- the optical properties such as the optical radius of curvature, enable autofocusing of the biometrics of the region of interest.
- the micromotor here may be a voice coil motor (VCM) as shown in Fig. 4, which is a device for converting electrical energy into mechanical energy.
- VCM voice coil motor
- the operation of the VCM includes a current passing through an electromagnetic (coil). This will create an electromagnetic field that repels the permanent magnets, thereby enabling the optical lens holder to be moved vertically away from the image sensor.
- the restoring force provided by the spring by the VCM causes the optical lens to approach the image sensor; while the rest of the optical lens is infinitely in focus.
- VCM becomes an obstacle to achieve this. Specifically, to make the VCM smaller, smaller coils, magnets and springs are needed. Since the magnetic force is proportional to the volume, smaller turns and magnets require more current to generate enough actuation force, which will make the problem of power consumption and overheating of the mobile terminal more serious. In addition, smaller springs are more fragile, exacerbating stroke lag, lens tilt, and reliability issues. Since the VCM suffers from stroke lag, it will slow the autofocus process, which This kind of problem becomes especially prominent during video capture. In addition, the high power consumption of the VCM will quickly drain the battery and the heat generated will also degrade the optical performance and imaging quality of the biometric imaging device.
- the micro-motor can also use the MEMS Actuators as shown in Figure 5, the structure of which includes a silicon wafer-based MEMS actuator (by a vertically movable housing)
- the structural components, the spring-loaded actuator that provides the stress-relieving spring, and the control housing structure are manufactured using a semiconductor process with mechanical and electrical properties.
- the comb drive is a pair of electrically conductive structures that create an attractive force that causes the comb drives to be pulled together when a DC voltage is applied.
- the biometric-based image processing algorithm combines accurate position-aware positioning algorithms in a very short time.
- the silicon MEMS autofocus actuator can control any of the optical lens groups. The position of one or more lenses moves, while the other lenses can be held in their optimal position to remain stationary, enabling efficient autofocus.
- MEMS actuators can combine the three components (coils, magnets and springs) required in the VCM into a single component, solving the complex physical connection between the three VCM components. Smaller, reducing the effects of physical inertia between them, enabling faster focusing, 2-4 times faster than normal VCM focusing. At the same time, semiconductor technology is used to manufacture, especially lithography, so power consumption can be controlled to be smaller.
- the biometric imaging device of the present disclosure avoids autofocusing by conventionally measuring the physical distance between the imaging device and the subject, thereby There is no need to configure the hardware required for ranging, such as ranging sensors.
- the biometric imaging device uses a micro motor to replace the stepper motor or the DC motor to adjust the optical lens component.
- the biometric imaging apparatus 100 obtains the step size of the moving optical lens component based on the image quality information of the electronic image, and adjusts the position of the optical lens component according to the step size to move the fixed imaging focal plane of the optical lens component to Achieve autofocus.
- the step size here includes the direction in which the optical lens component moves (such as facing the biometric direction forward or backward) and the distance.
- the biometric imaging apparatus 100 compares the image quality information with the ⁇ lookup table of the entire optical imaging system, According to this, the displacement state of the current optical imaging system is obtained, so that the displacement quantity information, that is, the step size, which needs to be changed to achieve the clear focus imaging state is obtained by the lookup table. Then, the biometric imaging apparatus 100 controls and rapidly adjusts the position of the imaging focal plane of the optical lens component in accordance with the step size to effect autofocus control of the biometrics of the region of interest.
- the biometric imaging apparatus 100 may first control and adjust the position of the imaging focal plane of the optical lens component in one direction according to a predetermined step to obtain another The electronic image is framed, and the image quality information of the electronic image of the other frame is obtained in the same manner as before.
- the biometric imaging device 100 compares the image quality information of the two frames of the previous and second frames, and if the adjusted frame image quality is improved compared to the frame image quality before the adjustment, the biometric imaging device 100 is in focus, and continues to exceed this.
- the direction moves by a predetermined step size, otherwise it moves in the opposite direction until the image quality information that satisfies the requirements is obtained.
- the space for moving the optical lens unit becomes smaller. In this case, it becomes more difficult to achieve autofocus by moving the optical lens unit.
- the optical lens component in the biometric imaging apparatus 100 is implemented by using a liquid lens, and the micromotor is driven to change the shape of the liquid lens according to image quality information of the electronic image, thereby adjusting the optical lens.
- the optical properties of the component such as the optical radius of curvature, for autofocus.
- the biometric imaging device 100 compares the image quality information with the ⁇ lookup table of the entire optical imaging system, and obtains the optical curvature state of the current optical imaging system.
- the biometric image forming apparatus 100 drives the micromotor to change the shape of the liquid lens in accordance with the optical radius of curvature, thereby causing the optical lens component to have the corresponding optical characteristic.
- the force required to change the shape of the optical lens to adjust its optical characteristics is much less than the force required to move the position of the optical lens, which will save power consumption of the micro-motor.
- device power consumption is an important metric to measure applicability, while low-power biometric imaging devices will meet this requirement, making them suitable for use as a portable device alone or integrated into other portable devices, such as smart Telephone, etc.
- the biometric imaging & preparation 100 can be derived from Determining a specific physical attribute of the biometric having a relatively objective constant value, obtaining an attribute value of the specific physical attribute in the image as image quality information of the image, and then adjusting the optical lens component according to the attribute value to implement The biometrics of the region of interest are subjected to autofocus control.
- the biometric imaging device 100 may first locate a biometric in an electronic image by using the aforementioned image analysis algorithm, and query a biometric-specific attribute list for a relatively objective constant value corresponding to the biometric according to the biometric feature.
- a biometric-specific attribute list for a relatively objective constant value corresponding to the biometric according to the biometric feature.
- relative objective constant value means that the value of a particular physical property of a biological feature changes little in the objective world, and does not vary greatly depending on the host of the biological feature.
- the biometric in the image is a human binocular iris (ie, the eyes of the person are included in the image)
- the specific attribute corresponding to the binocular iris can be queried to obtain the pupil spacing (as shown in FIG. 1), because the pupil spacing of the normal person changes. Very small, can be considered constant.
- the biometric imaging device 100 can calculate the attribute value of the particular physical property in the electronic image. For example, the biometric imaging device 100 can calculate the pixel distance value of the pupil's pupil spacing in the electronic image.
- the biometric imaging apparatus 100 may obtain an attribute value of a specific physical attribute in the electronic image based on the calculation, such as a pixel distance value of the pupil distance /?, and calculate a substance between the biometric of the region of interest and the biometric imaging apparatus 100.
- the distance D such as the distance from the iris plane of the human eye to the optical lens component.
- the optical characteristic parameters of the optical lens component are known, the optical field of view is known, and the pupil spacing P is substantially constant, and the variation thereof has a small influence on the calculation of the object distance D. Therefore, the object distance D and the pixel spacing of the pupil are The distance value can be regarded as an inverse relationship, and the object distance D can be calculated by the energy transfer function as described above.
- the biometric imaging apparatus 100 can adjust the optical lens section to achieve autofocus based on the calculated object distance D and the current imaging focal length d of the optical lens component.
- the biometric imaging apparatus 100 can drive the micromotor to move the optical lens component to a specified position in accordance with the step length L to complete the autofocus.
- the biometric image forming apparatus 100 may adjust the optical curvature radius of the liquid lens by driving the micromotor to change the shape of the liquid lens to make the optical lens component The value of the imaging focal length d approaches the object distance Z), thereby completing the autofocus.
- biometric imaging device can be integrated into mobile terminals such as smart phones, tablets, ultrabooks, notebook computers, smart wearable devices, etc., thereby providing various convenient applications due to its small size and fast recognition speed.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Multimedia (AREA)
- General Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Ophthalmology & Optometry (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Theoretical Computer Science (AREA)
- Optics & Photonics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Studio Devices (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
本发明的目的是提供一种生物特征成像设备,其中该设备包括:光学镜头部件,用于对感兴趣区域的生物特征进行光学成像(包括静态图像和动态图像);图像传感器,用于将所述生物特征的光学图像转换成电子图像(包括静态图像和动态图像);以及微电机控制器,用于获取、传递、或分析电子图像的图像质量信息,并根据电子图像的图像质量信息实时分析图像的清晰度,实时反馈该信息从而调节光学镜头部件以实现对感兴趣区域的生物特征进行自动对焦控制。
Description
一种生物特征成像的方法与设备 技术领域
本发明涉及光学技术领域, 尤其涉及一种对生物特征进行成像的 技术。 背景技术
虹膜识别是一种新兴的生物识别技术, 在身份识别领域应用不断 扩大。 安全便捷的身份识别是开展面向移动终端业务服务的难点。 目 前用移动终端作为身份确认的手段主要依赖密码和卡, 存在难记忆、 易被窃取, 安全性低等问题。 在众多身份识别技术中, 虹膜识别的安 全性和精确度最高, 具有个体唯一、 不需要记忆、 不能被窃取, 安全 级别高等优点。
在现有技术中, 虹膜成像设计一般采用定焦设计, 用户需要主动 配合来寻找合适的虹膜成像位置, 导致需要附加额外的硬件设备如测 距传感器、 三色指示灯等; 也有些虹膜成像系统采用步进电机或者直 流电机来驱动镜头的前后移动实现虹膜自动对焦和成像, 但仍然需要 测距传感器来测量距离, 并且步进电机或者直流电机的体积大, 功耗 大。 这些均导致虹膜成像系统的体积大大增加, 识别速度拉长, 用户 体验差, 无法微型化集成应用到需求量更广的移动终端。 发明内容
本公开的目的在于提供一种生物特征成像方法和设备以及包含该 设备的移动终端, 从而减轻或消除上面提及的一个或者多个问题。
根据本公开的一个方面, 提供了一种生物特征成像设备, 其中该 设备包括: ,
光学镜头部件, 用于对感兴趣区域的生物特征进行光学成像; 图像传感器, 用于将包含所述生物特征的光学图像转换成电子图 像;
微电机, 用于调节所述光学镜头部件; 以及
微电机控制器, 用于获取所述电子图像的图像质量信息, 根据所 述电子图像的图像质量信息控制微电机调节所述光学镜头部件以实现
对所述感兴趣区域的生物特征进行自动对焦控制。
根据本公开的另一方面, 还提供了一种移动终端, 其中该移动终 端包括如上所述的生物特征成像设备。
根据本公幵的又一方面, 还提供了一种生物特征成像方法, 其中 该方法包括以下步骤:
获取通过光学镜头部件捕获的感兴趣区域的生物特征的图像; 获取所述图像的图像质量信息; 以及
根据所述图像的图像质量信, 控制微电机调节所述光学镜头部件 以实现对所述感兴趣区域的生物特征进行自动对焦控制。
与现有技术相比, 本公开能够根据生物特征的电子图像的图像质 量信息对该生物特征进行自动对焦控制, 避免了传统地通过测量成像 设备与被摄体之间的物理距离进行自动对焦, 从而不需要配置测距所 需的硬件, 例如测距传感器。 另外, 本公开采用微型电机以替代步进 电机或者直流电机来调节光学镜头部件。 这些都为生物特征成像设备 的小型化提供了可能。 附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描 述, 本发明的其它特征、 目的和优点将会变得更明显:
图 1示出根据本公开一个方面的生物特征成像设备示意图; 图 2示出根据本公开另一方面的生物特征成像设备示意图; 图 3示出根据本公开一个方面的生物特征成像方法流程图; 图 4示出根据本公开实施例的音圈电机的示意图;
图 5示出根据本公开实施例的微机电系统致动器的示意图; 图 6 示出根据本公开实施例的双眼分割定位成左右眼两个单独的 单眼虹膜图像的示意图。
附图中相同或相似的附图标记代表相同或相似的部件。 具体实施方式
本领域的技术人员应当明白本发明可以以脱离这些具体细节的其 它实现方式来实现。 而且为了不模糊本发明, 在当前的说明中省略了 已知的功能和结构的并非必要的细节。
下面结合附图对本公开作进一步详细描述。
图 1示出根据本公开一个方面的生物特征成像设备示意图。如图 1 所示,生物特征成像设备 100包括光学镜头部件 1 10 , 图像传感器 120, 微电机 140以及微电机控制器 130。
光学镜头部件 1 10用于对感兴趣区域 13 的生物特征 12进行光学 成像。
具体地, 光学镜头部件 1 10 可以是光学镜头组, 其实现在一个固 定成像焦平面的生物特征信息的成像。 光学镜头组的材料可以采用全 玻璃镜头、 全塑料镜头、 玻璃与塑料镜头相结合或者液体镜头等混合 材料。 在本文中, 将虹膜作为生物特征的实例来描述本公开的实施例, 但本领域技术人员应当理解, 生物特征还包括视网膜、 眼纹、 唇紋、 面部以及静脉等。 感兴趣区域 13指代光学镜头部件成像能够保持聚焦 清晰的区域, 即光学镜头部件能够对位于感兴趣区域中的生物特征进 行清晰成像。 感兴趣区域 13的大小根据光学镜头部件的景深确定, 景 深是指成像系统能够保持聚焦清晰的最近和最远的距离之差。 它决定 了用户可以距离生物特征成像设备的远近的冗余度范 , 或者是生物 特征识别的使用范围。 另外, 光学成像原理是本领域公知的技术, 为 了简洁起见, 在此不再赘述。
图像传感器 120用于将从光学镜头部件 1 10获取的生物特征的光 学图像转换成电子图像。
具体地, 图像传感器 120 可以包括电荷耦合元件 (CCD ) 和金属 氧化物半导体元件(CMOS )等感光元件, 并利用感光元件将生物特征 的光学成像转换成电子信号以获得相应的电子图像。 在一个实施例中, 电子图像包括静态图像和动态图像格式, 动态图像是由多帧静态图像 按照时间顺序排列组合在一起的静态图像流, 也称视频格式。 电子图 像可以被存储成预定的图像格式, 包括但不限于 BMP, JPEG、 TIFF , RAW, GIF和 PNG等。 电子图像的信息也可以以二进制比特的表征形 式保存在緩存或者内存中, 比如每个图像像素使用 8 特, 10比特, 12 比特,或者 24比特的二进制信息来代表,这些信息会作为后续生物图像 分析、 识别等的基本处理信息。
本领域技术人员应当理解, 上述将光学图像转换成电子图像的方 式仅为举例, 其他现有的或今后可能出现转换方式如可适用于本发明,
也应包含在本发明保护范围以内, 并在此以引用方式包含于此。
微电机控制器 130用于获取、 传递、 或分析图像传感器 120转换 的电子图像(包括静态图像和动态图像)的图像(或视频)质量特征信息, 然后, 根据所述电子图像的图像、 视频质量信息实时分析图像的生物 特征或清晰度并利用微电机 140调节光学镜头部件 1 10的成像组件特 性以实现对所述感兴趣区域的生物特征进行自动对焦控制。
具体地, 微电机控制器 130例如可以从图像传感器 120获取电子 图像, 并对该电子图像进行评估以获得该电子图像的图像质量特征信 息, 例如图像的清晰度、 或生物特征。 在对电子图像质量进行评估时, 可以对电子图像整体进行评估, 以获得该电子图像的整体图像质量信 息; 也可以首先识别出电子图像中所包含的生物特征 (例如虹膜) 图 像, 然后评估该生物特征图像以获得该生物特征的图像质量信息, 并 将其作为所述电子图像的图像质量信息。 所述图像质量信息包括但不 限于图像的清晰度、 对比度、 平均灰度、 图像信息熵、 瞳孔间距、 瞳 孔直径、 虹膜直径、 水平眼角宽度等。
例如, 针对图像传感器 120 所采集得到的任一帧电子图像, 微电 机控制器 130 可以快速定位到所感兴趣的生物特征区域, 比如人眼的 虹膜区域。 以虹膜为例, 所述微电机控制器 130 能够对人的双眼区域 同时成像, 针对每一帧采集的图像, 采用图像处理的算法实时计算出 人左右眼的瞳孔中心位置, 从而实现在整幅成像图像上双眼虹膜的实 时查找和实时定位, 并将所述成像图像裁剪为左眼或右眼的单眼虹膜 图像, 如图 6所示, 图像分辨率一般为 640 x 480。 这样图像分割后所 得到的左右眼的单眼的虹膜图像,可以作为所述生物特征成像设备 100 采集影像清晰度评估的一个分析对象。 然后的, 针对任意一个单眼或 双眼的虹膜进行图像分析其图像质量函数 ImageQualityMetncs, 该函 数的计算可以通过多种能量传递函数 F实现, 包括但不限于离散余弦 变换 (DCT ) , 快速傅立叶变换 (FFT ) 或者小波变换 (Wavelet ) 等。 计算得到的图像质量信息可以是一组图像质量数组, 也可以是单一图 像质量参数, 包括但不限于图像的清晰度、 对比度、 平均灰度、 图像 信息熵、 瞳孔间距、 瞳孔直径、 虹膜直径等。
需要指出的是, 以上从电子图像中识别生物特征的图像处理算法 例如参见中国专利申请 CN102855476A 中的图像处理过程, 该专利申
请将作为本说明书的一部分全文引用于此。 然而, 本领域技术人员应 当理解, 上述图像处理的方式仅为举例, 其他现有的或今后可能出现 图像处理方式如可适用于本发明, 也应包含在本发明保护范围以内, 并在此以引用方式包含于此。
可替换地, 微电机控制器 130 也可以将电子图像发送给第三方图 像质量评估设备 (比如计算机、 处理器、 服务器等未示出) , 该第三 方图像质量评估设备接收该电子图像并对其进行评估以获得图像质量 信息, 然后将该图像盾量信息反馈给微电机控制器 130。
在获得电子图像的图像盾量信息后, 微电机控制器 130 例如可以 对电子图像的图像质量信息以及图像生物特征信息进行分析, 并据此 控制微电机 140移动光学镜头部件 1 10或光学镜头部件 1 10 中光学透 镜的位置, 或改变光学镜头部件 110 的光学特性, 如光学曲率半径。 这样, 例如多次重复上述过程从而实现对感兴趣区域的生物特征的自 动对焦。 具体实现过程将在下文中详细描述。
微电机 140 用于调节光学镜头部件 1 10, 例如移动光学镜头部件 1 10或光学镜头部件 1 10中光学透镜的位置,或者例如通过改变光学镜 头部件 1 10 中光学透镜的形状而改变光学镜头部件 1 10 的光学特性, 如光学曲率半径。
这里, 微电机 140可以是如图 4所示的音圈电机 (VCM), 它是一 种将电能转化为机械能的装置, 具体地, VCM的操作包括是电流通过 电磁 (线圈) 。 这将产生排斥永磁体的电磁场, 从而实现垂直地移动 光学透镜夹持器使光学透镜远离图像传感器。 VCM由弹簧提供的恢复 力使光学透镜接近图像传感器; 而其余的光学透镜的位置是无限远对 焦。
当考虑保证成像质量的情况下将生物特征成像设备 100 集成在更 薄的移动终端(如手机)时, VCM会成为实现此目的的障碍。 具体地, 若要将 VCM做的更小, 则需要更小的线圈, 磁体和弹簧。 由于磁力是 与体积成正比的, 所以更小的线圈和磁体需要更多的电流才能产生足 够的致动力, 这将使移动终端的功耗和过热的问题更加严重。 此外, 较小的弹簧较为脆弱, 加剧了冲程迟滞、 镜头倾斜以及可靠性的问题。 由于 VCM遭受冲程迟滞的问题,所以将使针对感兴趣的生物特征区域 (比如虹膜) 的自动对焦成像过程变得緩慢, 这样的问题在视频捕获
时变得尤为突出。 另外, VCM的高功耗将迅速消耗电池并且产生的热 量也将降低生物特征成像设备的光学性能和成像质量。
为解决以上问题, 电机 140还可以采用如图 5 所示的微机电系 统致动器 (MEMS Actuators),其结构包括一个以,硅晶圆为基础的微机电 机械执行器 (由可垂直移动的外壳结构组件、 提供恢复应力的弹簧和 控制外壳结构组件的静电梳状驱动器组成), 采用半导体工艺来制造, 有机械和电子特性。 梳状驱动器是一对导电结构, 当施加直流电压时, 静电荷所产生的吸引力使梳状驱动器被拉到一起。 通过将光学透镜放 置在中心位置, 基于生物特征的图象处理算法会在极短的时间内运算 结合精确的位置感知定位算法, 硅微机电系统自动对焦致动器可以控 制光学镜片组中其中任何一片镜片或多片镜片的位置移动, 而其他的 镜片可以固定在其最佳位置保持不动, 从而实现高效的自动对焦。
相较于 VCM, 微机电系统致动器能够将 VCM里面所需要的三个 部件 (线圈, 磁体和弹簧) 整合成为一个单一组件, 解决了 VCM三 个组件之间的复杂物理连接, 体积做到更小, 减小了它们之间的物理 惯性应力影响, 从而能够更加快速的对焦, 比普通 VC:M对焦的控制速 度能够快 2-4倍。 同时采用半导体工艺来制造, 特别是光刻技术, 所 以功耗能够控制到更小。
由于能够根据生物特征的电子图像的图像质量信息对该生物特征 进行自动对焦控制, 本公开的生物特征成像设备避免了传统地通过测 量成像设备与被摄体之间的物理距离进行自动对焦, 从而不需要配置 测距所需的硬件, 例如测距传感器。 另外, 该生物特征成像设备采用 微型电机以替代步进电机或者直流电机来调节光学镜头部件。 这些都 为生物特征成像设备的小型化提供了可能。 '
可选地, 生物特征成像设备 100 的各个装置之间是持续不断工作 的。 具体地, 光学镜头部件 1 10 对感兴趣区域的生物特征进行光学成 像; 随后, 图像传感器 120 将所述生物特征的光学图像转换成电子图 像; 接着, 微电机控制器 130 获取电子图像的图像质量信息, 并根据 电子图像的图像质量信息分析从而调节光学镜头部件。 在此, 本领域 技术人员应理解 "持续" 是指各装置分别按照设定的或实时调整的工 作模式要求进行对感兴趣区域的生物特征的光学成像、 将光学图像转 换成电子图像, 并根据电子图像的图像质量信息分析调节光学镜头部
件直到实现对所述生物特征的期望对焦。
在一个实施例中, 微电机控制器 130 根据电子图像的图像质量信 息获得移动光学镜头部件 1 10 的步长, 并按照所述步长调节光学镜头 部件 1 10 的位置从而移动光学镜头部件 1 10的固定成像焦平面以实现 自动对焦。 具体地, 这里的步长包括光学镜头部件 1 10移动的方向(如 面向生物特征方向向前或向后) 和距离。
例如, 在获得电子图像的图像质量信息后, 微电机控制器 130 将 该图像质量信息与整个光学成像系统(即光学镜头部件 1 10 )的经验查 找表进行对比查找, 并据此得到当前的光学成像系统的位移状态, 从 而通过查找表得到实现清晰聚焦成像状态所需要改变的位移数量信 息, 即步,长。 然后, 微电机控制器 130 按照该步长控制并迅速调节所 述光学镜头部件的成像焦平面的位置以实现对所述感兴趣区域的生物 特征进行自动对焦控制。
再如, 在获得一帧电子图像的图像质量信息后, 微电机控制器 130 可以先按照预定的步长朝着一个方向控制并迅速调节所述光学镜头部 件的成像焦平面的位置来获得另一帧电子图像, 并采用与前面相同的 方法获得该另一帧电子图像的图像质量信息。 接着, 微电机控制器 130 将前后两帧电子图像的图像质量信息进行比较, 如果调节后的帧图像 质量比调节前的帧图像质量有提高, 说明微电机控制器 130对焦正确, 并继续超这个方向移动预定的步长, 否则朝着反方向移动, 多次重复 直到获得满足要求的图像质量信息。
为了使生物特征成像设备 100更加小型化,移动光学镜头部件 1 10 的空间以及光学镜头部件 1 10 本身将变得更小。 在此情况下, 通过移 动光学镜头部件或光学镜头部件中的光学透镜来实现自动对焦将变得 更加困难。 为解决此问题, 在一个实施例中, 生物特征成像设备 100 中的光学镜头部件 1 10采用液体镜头来实现,并且其微电机控制器 130 根据电子图像的图像质量信息来驱动微电机 140 改变该液体镜头的形 状, 从而调节光学镜头部件 1 10 的光学特性, 如光学曲率半径, 以实 现自动对焦。 例如, 在获得电子图像的图像质量信息后, 微电机控制 器 130将该图像质量信息与整个光学成像系统 (即光学镜头部件 1 10 ) 的经验查找表进行对比查找, 并据此得到当前的光学成像系统的光学 曲率状态, 从而通过查找表得到实现清晰聚焦成像状态所需要改变的
光学曲率半径。 然后, 微电机控制器 130 按照该光学曲率半径驱动微 电机 140 改变该液体镜头的形状, 从而使光学镜头部件 1 10具有该相 应的光学特性。
如本领域技术人员所知, 改变光学镜头形状以调节其光学特性所 需的力远小于移动光学镜头位置所需的力, 这将节省微电机的功耗。 对于便携式设备而言, 设备功耗是衡量其适用性的重要指标, 而低功 耗的生物特征成像设备将满足这方面的要求, 从而适于单独作为便携 式设备或集成到其他便携式设备, 如智能电话等。
可选地, 在一个实施例中, 微电机控制器 130 可以从电子图像中 确定生物特征的具有相对客观恒定数值的特定物理属性, 获取该特定 物理属性在电子图像中的属性值作为所述电子图像的图像质量信息, 然后根据属性值调节所述光学镜头部件以实现对所述感兴趣区域的生 物特征进行自动对焦控制。
具体地, 微电机控制器 130 首先可以通过前述的图像分析算法定 位电子图像中生物特征, 并根据该生物特征例如在生物特征特定属性 列表中查询与该生物特征相对应的具有相对客观恒定数值的特定物理 属性。 这里所说的 "相对客观恒定数值" 是指生物特征的特定物理属 性的数值在客观世界中变化很小, 其不随着生物特征的宿主的不同而 发生较大变化。 例如, 当电子图像中的生物特征为人类双眼虹膜 (即 电子图像中包括人的双眼) 时, 可以查询获得与双眼虹膜对应的特定 属性为瞳孔间距 ? (如图 1所示) , 因为正常人瞳孔间距 变化很小, 可视为恒定。
在确定生物特征的特定物理属性后, 由于生物特征成像设备 100 的光电传递函数已知, 微电机控制器 130 可以计算该特定物理属性在 电子图像中的属性值。 例如, 微电机控制器 130 可以计算人的瞳孔间 距在电子图像中的像素距离值/ 。
接着, 微电机控制器 130 可以基于计算获得特定物理属性在电子 图像中的属性值, 如瞳孔间距的像素距离值/ , 计算感兴趣区域 13的 生物特征与生物特征成像设备 100之间的物距 Z), 如人眼虹膜平面 12 到光学镜头部件 1 10或者图像传感器 120的距离。 例如, 光学镜头部 件 1 10 的光学特性参数已知, 其光学视场角 1 1 已知, 而且人瞳孔间 距 基本恒定, 其变化对于计算物距 D影响 ^艮小, 因此, 物距 D和人
瞳孔间距的像素距离值 可视为成反比关系, 即分析计算得到的人瞳 孔间距的像素距离值 /7 ' 越大,人眼离成像设备 100的距离约小(近); 分析计算得到的人瞳孔间距的像素距离值 越小, 人眼离成像设备
100的距离约大(远); 因此可通过如前所述的传递函数 计算出物距 D, 即
D =F ( ρ' ) 而且这个传递函数 F 针对不同的成人变化很小, 因此可以视为经 验函数恒定不变, 对成年人普遍适用。
然后, 微电机控制器 130可以根据计算荻得的物距 D和光学镜头 部件 1 10当前的成像焦距 d来比较从而有目的地调节所述光学镜头部 件 1 10以实现自动对焦。 例如, 微电机控制器 130可以计算物距 D和 成像焦距 ι之差 L ( L= D- fd ) , 此 就是使光学镜头部件 1 10能够 对感兴趣区域的生物特征进行清晰成像所需要移动的对焦向量, 因此 移动光学镜头部件 1 10的步长即为 。 在此情况下, 微电机控制器 130 可以按照该步长 L驱动微电机将光学镜头部件 1 10移动到指定位置从 而完成自动对焦。 可替换地, 例如, 当光学镜头部件 1 10 的光学镜头 组中包含液体镜头时, 微电机控制器 130可以通过驱动微电机 140改 变液体镜头的形状来调整该液体镜头的光学曲率半径以使得改变后的 光学镜头部件 1 10新的成像焦距 d的值趋近于物距 , 从而完成自动 对焦。
可选地, 如图 2所示, 生物特征成像设备 100还可以包括一个或 多个照明部件 150 ,用于在对感兴趣区域中的生物特征进行光学成像时 对感兴趣区域进行照明, 以增强采集图像的亮度。
照明部件 150 例如可以是发光二极管 (LED ) , 也可以是其他种 类的照明器件, 并且照明部件 150 可以采用可见光或近红外光进行照 明。 照明部件 150在生物特征成像设备 100上的位置可以距离光学镜 头部件 1 10等间距放置,也可以围绕光学镜头部件 1 10 360度任意放置, 间距任意。
照明部件 150 所发出的光的中心光谱可以根据具体待成像的生物 特征进行设定。 例如, 若生物特征为虹膜, 则采用的近红外光的中心
光语范围包括 700nm至 950nm。
进一步地, 当对人体虹膜进行成像时, 由于不同人种的虹膜特征 (例如颜色) 不尽相同, 为了实现对不同人种的虹膜进行清晰成像, 可以采用不同中心光谱的照明部件对其进行照明。 例如, 生物特征成 像设备 100包括三个发射近红外光的 LED灯,每个 LED灯发射的近红 外光的中心光谱分别为 780nm和 850nm和 940nm, 以便对不同人种深 浅不同的虹膜进行更好的成像照明。
在一个实施例中, 生物特征成像设备 100 可以对单眼虹膜进行成 像, 也可以对双眼虹膜同时进行成像。
例如, 若对单眼虹膜进行清晰成像以用于虹膜识别, 则光学镜头 部件 1 10在眼睛水平方向的光学分辨率需大于等于 640像素, 垂直方 向的光学分辨率需大于等于 480像素。 相应地, 图像传感器 120的图 像分辨率需大于或等于光学镜头部件的光学分辨率。
若需对双眼虹膜进行一次清晰成像以用于汉眼虹莫识别, 则光学 镜头部件 1 10在双眼水平方向的光学分辨率需大于等于 1500像素, 垂 直方向的光学分辨率需大于等于 480 像素, 从而保证每只单眼的图像 的光学分辨率。 相应地, 图像传感器 120 的图像分辨率需大于或等于 光学镜头部件的光学分辨率。
可选地, 生物特征成像设备 100 还包括滤光片 (未示出) , 其位 于待成像生物特征和光学镜头部件之间, 以过滤该生物特征进入光学 镜头部件 1 10 的光, 从而能够降低外界环境对生物特征成像的影响, 特别是室外环境太阳光、 杂散光、 灯光和黑暗环境。
图 3 示出根据本公开一个方面的生物特征成像方法流程图。 现参 照图 1和图 3描述该生物特征成像方法的处理过程。
在步骤 310 ,生物特征成像设备 100获取通过光学镜头部件捕获的 感兴趣区域的生物特征的图像。
例如, 生物特征成像设备 100 可以利用光学镜头部件,如光学镜头 组对感兴趣区域的生物特征进行光学成像。 光学镜头组的材料可以采 用全玻璃镜头、 全塑料镜头、 玻璃与塑料镜头相结合或者液体镜头等 混合材料。 在本文中, 将虹膜作为生物特征的实例来描述本公开的实 施例, 但本领域技术人员应当理解, 生物特征还包括见网膜、 眼纹、 唇纹、 面部以及静脉等。 感兴趣区域指代成像能够保持聚焦清晰的区
域, 即生物特征成像设备 100 能够对位于感兴趣区域中的生物特征进 行清晰成像。 可选地, 在对感兴趣区域的生物特征进行光学成像时, 可以采用可见光或近红外光对被摄对象进行照明, 以便获得更高的光 学成像质量。
随后, 生物特征成像设备 100 可以利用电荷耦合元件 (CCD ) 和 金属氧化物半导体元件( CMOS )等感光元件将生物特征的光学成像转 换成电子信号以获得相应的电子图像, 该电子图像即为要获取的生物 特征的图像。 在一个实施例中, 电子图像包括静态图像和动态图像格 式, 动态图像是由多帧静态图像按照时间顺序排列组合在一起的静态 图像流, 也称视频格式。 电子图像可以被存储成预定的图像格式, 包 括但不限于 BMP, JPEG、 TIFF, RAW, GIF和 PNG等。 电子图像的信 息也可以以二进制比特的表征形式保存在緩存或者内存中, 比如每个 图像像素使用 8比特, 10比特, 12比特,或者 24比特的二进制信息来代 表, 这些信息会作为后续生物图像分析、 识别等的基本处理信息。
本领域技术人员应当理解, 上述将光学图像转换成电子图像的方 式仅为举例, 其他现有的或今后可能出现转换方式如可适用于本发明, 也应包含在本发明保护范围以内, 并在此以引用方式包含于此。
本领域技术人员应当理解, 上述获取感兴趣区域的生物特征的图 像的方式仅为举例, 其他现有的或今后可能出现转换方式如可适用于 本发明, 也应包含在本发明保护范围以内, 并在此以引用方式包含于 此。
在步骤 320 中, 生物特征成像设备 100获取在步骤 310 中获取的 生物特征的图像(包括静态图像和动态图像)的图像(或视频)质量信息。 例如, 生物特征成像设备 100 可以对电子图像整体进行评估, 以获得 该电子图像的整体图像质量信息; 也可以首先识别出电子图像中所包 含的生物特征 (例如虹膜) 图像, 然后评估该生物特 图像以获得该 生物特征的图像质量信息, 并将其作为所述电子图像的图像质量信息。 所述图像质量信息包括但不限于图像的清晰度、 对比度、 平均灰度、 图像信息熵等。
例如, 针对所述获得的任一帧电子图像, 生物特征成像设备 100 可以快速定位到所感兴趣的生物特征区域, 比如人眼的虹膜区域。 以 虹膜为例, 生物特征成像设备 100 能够对人的双眼区域同时成像, 针
对每一帧采集的图像, 采用图像处理的算法实时计算出人左右眼的瞳 孔中心位置, 从而实现在整幅成像图像上双眼虹膜的实时查找和实时 定位, 并将所述成像图像裁剪为左眼或右眼的单眼虹膜图像, 如图 6 所示, 图像分辨率一般为 640 X 480。 这样图像分割后所得到的左右眼 的单眼的虹膜图像, 可以作为所述生物特征成像设备 100 采集影像清 晰度评估的一个分析对象。 然后的, 针对任意一个单眼或双眼的虹膜 进行图像分析其图像质量函数 ImageQualityMetrics, 该函数的计算可 以通过多种能量传递函数实现, 包括但不限于离散余弦变换( DCT ) , 快速傅立叶变换 (FFT ) 或者小波变换 (Wavelet ) 等 计算得到的图 像质量可以是一组图像质量数组, 也可以是单一图像质量参数, 包括 但不限于图像的清晰度、 对比度、 平均灰度、 图像信息熵、 瞳孔间距 等。
在步骤 330, 生物特征成像设备 100根据所述电子图像的图像(或 视频) 质量信息并利用微电机设备调节光学镜头部件特性以实现对所 述感兴趣区域的生物特征进行自动对焦控制。
例如, 在获得电子图像的图像质量信息后, 生物特征成像设备 100 例如可以对电子图像的图像质量信息进行分析, 并据此驱动微电机产 生电磁力来移动光学镜头部件的位置或改变光学镜头部件的光学特 性, 如光学曲率半径, 从而实现对感兴趣区域的生物特征的自动对焦。 具体实现过程将在下文中详细描述。
这里的微电机可以是如图 4所示的音圈电机 (VCM), 它是一种将 电能转化为机械能的装置, 具体地, VCM的操作包括是电流通过电磁 (线圈) 。 这将产生排斥永磁体的电磁场, 从而实现垂直地移动光学 透镜夹持器使光学透镜远离图像传感器。 VCM由弹簧提供的恢复力使 光学透镜接近图像传感器; 而其余的光学透镜的位置是无限远对焦。
当考虑保证成像质量的情况下将生物特征成像设备 100 集成在更 薄的移动终端(如手机)时, VCM会成为实现此目的的障碍。 具体地, 若要将 VCM做的更小, 则需要更小的线圈, 磁体和弹簧。 由于磁力是 与体积成正比的, 所以更小的线圏和磁体需要更多的电流才能产生足 够的致动力, 这将使移动终端的功耗和过热的问题更加严重。 此外, 较小的弹簧较为脆弱, 加剧了冲程迟滞、 镜头倾斜以及可靠性的问题。 由于 VCM遭受沖程迟滞的问题, 所以将使自动对焦过程变得缓慢, 这
样的问题在视频捕获时变得尤为突出。 另外, VCM的高功耗将迅速消 耗电池并且产生的热量也将降低生物特征成像设备的光学性能和成像 质量。
为解决以上问题, 微电机还可以采用如图 5 所示的微机电系统致 动器 (MEMS Actuators) ,其结构包括一个以硅晶圆为基础的微机电机械 执行器 (由可垂直移动的外壳结构组件、 提供恢复应力的弹簧和控制 外壳结构组件的静电梳状驱动器组成) , 采用半导体工艺来制造, 有 机械和电子特性。 梳状驱动器是一对导电结构, 当施加直流电压时, 静电荷所产生的吸引力使梳状驱动器被拉到一起。 通过将光学透鏡放 置在中心位置, 基于生物特征的图象处理算法会在极短的时间内运算 结合精确的位置感知定位算法, 硅微机电系统自动对焦致动器可以控 制光学镜片组中其中任何一片镜片或多片镜片的位置移动, 而其他的 镜片可以固定在其最佳位置保持不动, 从而实现高效的自动对焦。
相较于 VCM, 微机电系统致动器能够将 VCM里面所需要的三个 部件 (线圈, 磁体和弹簧) 整合成为一个单一组件, 解决了 VCM 三 个组件之间的复杂物理连接, 体积做到更小, 减小了它们之间的物理 惯性应力影响, 从而能够更加快速的对焦, 比普通 VCM对焦的控制速 度能够快 2-4倍。 同时釆用半导体工艺来制造, 特别是光刻技术, 所 以功耗能够控制到更小。
由于能够根据生物特征的电子图像的图像质量信息对该生物特征 进行自动对焦控制, 本公开的生物特征成像设备避免了传统地通过测 量成像设备与被摄体之间的物理距离进行自动对焦, 从而不需要配置 测距所需的硬件, 例如测距传感器。 另外, 该生物特征成像设备采用 微型电机以替代步进电机或者直流电机来调节光学镜头部件。 这些都 为生物特征成像设备的小型化提供了可能。
在一个实施例中, 生物特征成像设备 100 根据电子图像的图像质 量信息获得移动光学镜头部件的步长, 并按照所述步长调节光学镜头 部件的位置从而移动光学镜头部件的固定成像焦平面以实现自动对 焦。 这里的步长包括光学镜头部件移动的方向 (如面向生物特征方向 向前或向后) 和距离。
例如, 在获得电子图像的图像质量信息后, 生物特征成像设备 100 将该图像质量信息与整个光学成像系统的经猃查找表进行对比查找,
并据此得到当前的光学成像系统的位移状态, 从而通过查找表得到实 现清晰聚焦成像状态所需要改变的位移数量信息, 即步长。 然后, 生 物特征成像设备 100 按照该步长控制并迅速调节光学镜头部件的成像 焦平面的位置以实现对所述感兴趣区域的生物特征进行自动对焦控 制。
再如, 在获得一帧电子图像的图像质量信息后, 生物特征成像设 备 100 可以先按照预定的步长朝着一个方向控制并迅速调节所述光学 镜头部件的成像焦平面的位置来获得另一帧电子图像, 并采用与前面 相同的方法获得该另一帧电子图像的图像质量信息。 接着, 生物特征 成像设备 100 将前后两帧电子图像的图像质量信息进行比较, 如果调 节后的帧图像质量比调节前的帧图像质量有提高, 说明生物特征成像 设备 100 对焦正确, 并继续超这个方向移动预定的步长, 否则朝着反 方向移动, 直到获得满足要求的图像质量信息。
为了使生物特征成像设备 100 更加小型化, 移动光学镜头部件的 空间变得更小。 在此情况下, 通过移动光学镜头部件来实现自动对焦 将变得更加困难。
为解决此问题, 在一个实施例中, 生物特征成像设备 100 中的光 学镜头部件采用液体镜头来实现, 并且根据电子图像的图像质量信息 来驱动微电机改变该液体镜头的形状, 从而调节光学镜头部件的光学 特性, 如光学曲率半径, 以实现自动对焦。 例如, 在获得电子图像的 图像质量信息后, 生物特征成像设备 100 将该图像质量信息与整个光 学成像系统的经猃查找表进行对比查找, 并据此得到当前的光学成像 系统的光学曲率状态, 从而通过查找表得到实现清晰聚焦成像状态所 需要改变的光学曲率半径。 然后, 生物特征成像设备 100 按照该光学 曲率半径驱动微电机改变该液体镜头的形状, 从而使光学镜头部件具 有该相应的光学特性。
如本领域技术人员所知, 改变光学镜头形状以调节其光学特性所 需的力远小于移动光学镜头位置所需的力, 这将节省微电机的功耗。 对于便携式设备而言, 设备功耗是衡量其适用性的重要指标, 而低功 耗的生物特征成像设备将满足这方面的要求, 从而适于单独作为便携 式设备或集成到其他便携式设备, 如智能电话等。
可选地, 在一个实施例中, 生物特征成像&备 100 可以从包含生
物特征的图像中确定生物特征的具有相对客观恒定数值的特定物理属 性, 获取该特定物理属性在图像中的属性值作为所述图像的图像质量 信息, 然后根据属性值调节光学镜头部件以实现对所述感兴趣区域的 生物特征进行自动对焦控制。
具体地, 生物特征成像设备 100 首先可以通过前述的图像分析算 法定位电子图像中生物特征, 并根据该生物特征例如在生物特征特定 属性列表中查询与该生物特征相对应的具有相对客观恒定数值的特定 物理属性。 这里所说的 "相对客观恒定数值" 是指生物特征的特定物 理属性的数值在客观世界中变化很小, 其不随着生物特征的宿主的不 同而发生较大变化。 例如, 当图像中的生物特征为人类双眼虹膜 (即 图像中包括人的双眼) 时, 可以查询获得与双眼虹膜对应的特定属性 为瞳孔间距 (如图 1 所示) , 因为正常人瞳孔间距 变化很小, 可 视为恒定。
在确定生物特征的特定物理属性后, 由于生物特征成像设备 100 的光电传递函数已知, 生物特征成像设备 100 可以计算该特定物理属 性在电子图像中的属性值。 例如, 生物特征成像设备 100 可以计算人 的瞳孔间距在电子图像中的像素距离值 , 。
接着, 生物特征成像设备 100 可以基于计算获得特定物理属性在 电子图像中的属性值, 如瞳孔间距的像素距离值 /?, , 计算感兴趣区 域的生物特征与生物特征成像设备 100之间的物距 D, 如人眼虹膜平 面到光学镜头部件的距离。 例如, 光学镜头部件的光学特性参数已知, 其光学视场角已知, 而且人瞳孔间距 P基本恒定, 其变化对于计算物 距 D影响 艮小, 因此, 物距 D和人瞳孔间距的像素距离值 , 可视为 成反比关系, 并可通过如前所述的能量传递函数 计算出物距 D, 即
D =F ( p, ) 然后, 生物特征成像设备 100可以根据计算获得的物距 D和光学 镜头部件当前的成像焦距 d来调节光学镜头部件以实现自动对焦。 例 如,生物特征成像设备 100可以计算物距 D和成像焦距 d之差 U = D- fd ) , 此 就是使光学镜头部件能够对感兴趣区域的生物特征进行清 晰成像所需要移动的对焦向量, 因此移动光学镜头部件的步长即为 。
在此情况下, 生物特征成像设备 100可以按照该步长 L驱动微电机将 光学镜头部件移动到指定位置从而完成自动对焦。 可替换地, 例如, 当光学镜头部件的光学镜头组中包含液体镜头时, 生物特征成像设备 100 可以通过驱动微电机改变液体镜头的形状来调整该液体镜头的光 学曲率半径以使得光学镜头部件的成像焦距 d的值趋近于物距 Z), 从 而完成自动对焦。
由于具有体积小、 识别速度快等优点, 因此上述生物特征成像设 备可以集成到诸如智能手机、 平板电脑、 超级本、 笔记本电脑、 智能 穿戴式设备等移动终端中, 从而提供各种便利的应用。
对于本领域技术人员而言, 显然本发明不限于上述示范性实施例 的细节, 而且在不背离本发明的精神或基本特征的情况下, 能够以其 他的具体形式实现本发明。 因此, 无论从哪一点来看, 均应将实施例 看作是示范性的, 而且是非限制性的, 本发明的范围由所附权利要求 而不是上述说明限定, 因此旨在将落在权利要求的等同要件的含义和 范围内的所有变化涵括在本发明内。 不应将权利要求中的任何附图标 记视为限制所涉及的权利要求。 此外, 显然 "包括" 一词不排除其他 单元或步骤, 单数不排除复数。 装置权利要求中陈述的多个单元或装 置也可以由一个单元或装置通过软件或者硬件来实现。 第一, 第二等 词语用来表示名称, 而并不表示任何特定的顺序。
Claims
1. 一种生物特征成像设备 ( 100) , 包括:
光学镜头部件( 110) , 用于对感兴趣区域(: 13 )的生物特征( 12) 进行光学成像;
图像传感器 ( 120) , 用于将包含所述生物特征( 12) 的光学图像 转换成电子图像;
微电机 ( 140) , 用于调节所述光学镜头部件 ( 110) ; 以及 微电机控制器 ( 130) , 用于获取所述电子图像的图像质量信息, 根据所述电子图像的图像盾量信息控制微电机 ( 140)调节所述光学镜 头部件 ( 110) 以实现对所述感兴趣区域 ( 13 ) 的生物特征 ( 12) 进行 自动对焦控制。
2. 根据权利要求 1 所述的设备, 其中所述微电机是音圈电机或微 机电系统致动器, 所述微电机进一步用于利用其产生的电磁力调节所 述光学镜头部件 ( 110) 从而实现对所述感兴趣区域( 13) 的生物特征 ( 12 ) 进行自动对焦控制。
3. 根据权利要求 1或 2所述的设备,其中所述微电机控制器( 130) 进一步用于根据所述电子图像的图像质量信息获得移动所述光学镜头 部件 ( 110) 的步长, 并按照所述步长调节所述光学镜头部件 ( 110) 的位置以实现自动对焦。
4. 根据权利要求 1或 2所述的设备,其中所述光学镜头部件( 110) 包括液体镜头, 所述微电机控制器 ( 130) 进一步用于根据所述电子图 像的图像质量信, 改变所述液体镜头的形状来调节所述光学镜头部件
( 110) 的光学特性以实现自动对焦。
5. 根据权利要求 1或 2所述的设备, 其中所述微电机控制器进一 步用于从所述电子图像中确定所述生物特征的具有相对客观恒定数值 的特定物理属性, 获取所述特定物理属性在所述电子图像中的属性值 作为所述电子图像的图像质量信息, 根据所述属性值调节所述光学镜 头部件 ( 110) 以实现对所述感兴趣区域 ( 13 ) 的生物特征 ( 12) 进行 自动对焦控制。
6. 根据权利要求 5所述的设备, 其中所述微电机控制器进一步用 于基于所述属性值计算所述感兴趣区域的生物特征与所述生物特征成
像设备 ( 100) 之间的物距, 根据所述物距和所述光学镜头部件 ( 110) 当前的成像焦距来调节所述光学镜头部件 ( 110) 以实现自动对焦。
7. 根据权利要求 6所述的设备, 其中所述微电机控制器进一步用 于计算所述物距与所述成像焦距之差以获得( 110)移动所述光学镜头 部件 ( 110) 的步长, 并按照所述步长移动所述光学镜头部件 ( 110) 的位置以实现自动对焦。
8. 根据权利要求 6所述的设备, 其中所述光学镜头部件( 110) 包 括液体镜头, 所述微电机控制器进一步用于根据所述物距和所述成像 焦距改变所述液体镜头的形状来调节所述光学镜头部件 ( 110) 的光学 特性以实现自动对焦。
9. 根据权利要求 5-8 中任一项所述的设备, 其中当所述生物特征 包括双眼虹膜时, 所述微电机控制器进一步用于从所述电子图像中确 定所述双眼虹膜的瞳孔间距为所述特定物理属性。
10. 根据权利要求 1或 2所述的设备,其中当所述生物特征包括 眼虹膜时, 所述光学镜头部件 ( 110) 在双眼水平方向的光学分辨率大 于等于 1500像素, 垂直方向的光学分辨率大于等于 480像素, 并且所 述图像传感器 ( 120 ) 的分辨率大于或等于所述光学镜头部件 ( 110) 的光学分辨率。
11. 根据权利要求 1或 2所述的设备,其中当所述生物特征包括单 眼虹膜时, 所述光学镜头部件 ( 110) 在眼睛水平方向的光学分辨率大 于等于 640像素, 垂直方向的光学分辨率大于等于 480 像素, 并且所 述图像传感器 ( 120) 的分辨率大于或等于所述光学镜头部件 ( 110) 的光学分辨率。
12. 根据权利要求 1至 11 中任一项所述的设备, 该设备还包括: 至少一个照明部件 ( 150) , 用于对所述感兴趣区域进行照明, 其 中所述至少一个照明部件 ( 150) 采用可见光和 /或近红外光照明。
13. 根据权利要求 12所述的设备, 其中当所述生物特征包括虹膜 时, 所述近红外光中心光讲范围包括 700nm至 950nmt.
14. 根据权利要求 13 所述的设备, 其中所述至少一个照明部件 ( 150 )采用不同中心光谱的近红外光来分别对不同特征的虹膜进行照 明。
15. 根据权利要求 1至 14中任一项所述的设备, 该设备还包括滤
光片以用于过滤进入所述光学镜头部件 ( 1 10 ) 的光。
16. 根据权利要求 1至 15 中任一项所述的设备, 其中所述生物特 征包括以下至少一项: 虹膜, 视网膜、 眼纹、 唇纹、 面部和静脉。
17. 一种移动终端, 所述移动终端包括如权利要求 1至 16中任一 项所述的生物特征成像设备。
18. 一种生物特征成像方法, 包括:
获取通过光学镜头部件捕获的感兴趣区域的生物特征的图像 ( 310 ) ;
获取所述图像的图像质量信息 ( 320 ) ; 以及
根据所述图像的图像质量信息控制微电机调节光学镜头部件以实 现对所述感兴趣区域( 13 )的生物特征( 12 )进行自动对焦控制( 330 )。
19. 根据权利要求 18所述的方法, 其中所述微电机是音圈电机或 微机电系统致动器, 所述自动对焦步骤包括利用所述微电机产生的电 磁力调节所述光学镜头部件。
20. 根据权利要求 18或 19所述的方法,其中所述自动对焦步骤包 括将根据所迷图像的图像质量信息获得移动所述光学镜头部件的步 长, 并按照所述步长调节所述光学镜头部件的位置以实现自动对焦。
21. 根据权利要求 18或 19所述的方法,其中所述光学镜头部件包 括液体镜头, 所述自动对焦步骤包括根据所述图像的 像质量信息改 变所述液体镜头的形状来调节所述光学镜头部件的光学特性以实现自 动对焦。
22. 根据权利要求 18或 19所述的方法,其中所述获取图像质量信 息的步骤 ( 320 ) 包括: 从所述图像中确定所述生物特征的具有相对客 观恒定数值的特定物理属性, 获取所述特定物理属性在所述图像中的 属性值作为所述图像的图像质量信息。
23. 根据权利要求 22所述的方法, 其中所述调节光学镜头部件的 步骤 ( 330 ) 包括: 基于所述属性值计算所述感兴趣区域的生物特征与 所述光学镜头部件之间的物距, 根据所述物距和所述光学镜头部件当 前的成像焦距来调节所述光学镜头部件以实现自动对焦。
24. 根据权利要求 23所述的方法, 其中所述根据所述物距和所述 成像焦距来调节所述光学镜头部件的步骤包括: 计算所述物距与所述 成像焦距之差以获得移动所述光学镜头部件的步长, 并按照所述步长
移动所述光学镜头部件的位置以实现自动对焦。
25. 根据权利要求 23所述的方法, 其中所述光学镜头部件包括液 体镜头, 所述根据所述物距和所述成像焦距来调节所述光学镜头部件 的步骤包括: 根据所述物距和所迷成像焦距改变所述液体镜头的形状 来调节所述光学镜头部件的光学特性以实现自动对焦。
26. 根据权利要求 22-25中任一项所述的方法, 其中当所述生物特 征包括双眼虹膜时, 所述确定所述生物特征的特定物理属性的步骤包 括: 从所述图像中确定所述双眼虹膜的瞳孔间距为所述特定物理属性。
27. 根据权利要求 18至 26中任一项所述的方法,该方法还包括采 用可见光和 /或近红外光对所述感兴趣区域进行照明。
28. 一种计算机程序产品, 包括指令, 当该指令在加载到计算设备 并在其上执行时, 导致该计算设备执行如权利要求 18-27所述的方法。
29. 一种计算机可读存储介质, 其中存储指令, 当该指令在加载到 计算设备并在其上执行时,导致该计算设备执行如权利要求 18-27所述 的方法。
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US14/648,368 US9852338B2 (en) | 2013-10-21 | 2014-03-26 | Biometric imaging method and device |
EP14856525.2A EP2924608A4 (en) | 2013-10-21 | 2014-03-26 | METHOD AND DEVICE FOR IMAGING BIOLOGICAL ELEMENTS |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310494298.1 | 2013-10-21 | ||
CN201310494298.1A CN103593647A (zh) | 2013-10-21 | 2013-10-21 | 一种生物特征成像的方法与设备 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2015058460A1 true WO2015058460A1 (zh) | 2015-04-30 |
Family
ID=50083779
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2014/000330 WO2015058460A1 (zh) | 2013-10-21 | 2014-03-26 | 一种生物特征成像的方法与设备 |
Country Status (4)
Country | Link |
---|---|
US (1) | US9852338B2 (zh) |
EP (1) | EP2924608A4 (zh) |
CN (2) | CN103593647A (zh) |
WO (1) | WO2015058460A1 (zh) |
Families Citing this family (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103593647A (zh) | 2013-10-21 | 2014-02-19 | 王晓鹏 | 一种生物特征成像的方法与设备 |
CN103870805B (zh) | 2014-02-17 | 2017-08-15 | 北京释码大华科技有限公司 | 一种移动终端生物特征成像方法和装置 |
CN104021382A (zh) * | 2014-06-20 | 2014-09-03 | 北京释码大华科技有限公司 | 一种眼部图像采集方法及其系统 |
CN104092987B (zh) * | 2014-07-10 | 2017-06-09 | 公安部第一研究所 | 一种双模双反馈自适应目标跟踪系统、控制电路及方法 |
US20160105285A1 (en) * | 2014-10-14 | 2016-04-14 | Qualcomm Incorporated | Deriving cryptographic keys from biometric parameters |
CN104735325B (zh) * | 2015-04-07 | 2018-01-26 | 北京释码大华科技有限公司 | 一种移动终端的成像设备及移动终端 |
CN104992141B (zh) * | 2015-05-29 | 2017-02-22 | 聚鑫智能科技(武汉)股份有限公司 | 基于双虹膜、立体人脸和声纹识别的智能生物特征监控总成及监控方法 |
TWI588585B (zh) * | 2015-06-04 | 2017-06-21 | 光寶電子(廣州)有限公司 | 影像擷取裝置及對焦方法 |
CN106303201A (zh) * | 2015-06-04 | 2017-01-04 | 光宝科技股份有限公司 | 影像撷取装置及对焦方法 |
KR102429427B1 (ko) * | 2015-07-20 | 2022-08-04 | 삼성전자주식회사 | 촬영 장치 및 그 동작 방법 |
CN105187734A (zh) * | 2015-07-23 | 2015-12-23 | 柳州永旺科技有限公司 | 一种动态图像与静态图像的加载方法 |
US10109126B2 (en) * | 2016-01-12 | 2018-10-23 | Chi-Wei Chiu | Biological recognition lock system |
WO2017132903A1 (zh) * | 2016-02-03 | 2017-08-10 | 徐鹤菲 | 与可见光复用的生物特征复合成像系统和方法 |
CN106210555B (zh) * | 2016-07-29 | 2017-11-24 | 广东欧珀移动通信有限公司 | 防炫光处理方法、装置和电子设备 |
CN106210527B (zh) * | 2016-07-29 | 2017-08-25 | 广东欧珀移动通信有限公司 | 基于mems移动的pdaf校准方法和装置 |
CN106901712A (zh) * | 2017-02-28 | 2017-06-30 | 广州医软智能科技有限公司 | 一种微循环成像装置 |
FR3069681B1 (fr) * | 2017-07-26 | 2021-12-17 | Safran Identity & Security | Procede et dispositif de capture d'image d'iris |
CN109409249A (zh) * | 2018-09-30 | 2019-03-01 | 联想(北京)有限公司 | 信息处理方法及电子设备 |
CN109101959B (zh) * | 2018-11-02 | 2024-08-09 | 张彦龙 | 一种基于液体透镜和vcm的虹膜图像提取装置 |
CN109480766A (zh) * | 2018-11-14 | 2019-03-19 | 深圳盛达同泽科技有限公司 | 视网膜自动对焦方法、装置、系统及眼底相机 |
JPWO2020261368A1 (zh) | 2019-06-25 | 2020-12-30 | ||
CN113536863A (zh) * | 2020-04-22 | 2021-10-22 | 上海聚虹光电科技有限公司 | 自适应虹膜灰度的光谱段选择方法 |
US11823488B1 (en) * | 2021-03-29 | 2023-11-21 | Amazon Technologies, Inc. | System for training embedding network |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1464323A (zh) * | 2002-06-13 | 2003-12-31 | 北京中星微电子有限公司 | 自动对焦技术 |
CN102855476A (zh) | 2011-06-27 | 2013-01-02 | 王晓鹏 | 单图像传感器自适应双眼虹膜同步采集系统 |
CN103136421A (zh) * | 2013-01-31 | 2013-06-05 | 沈洪泉 | 用于虹膜成像装置的系统级光电优化设计方法 |
CN103593647A (zh) * | 2013-10-21 | 2014-02-19 | 王晓鹏 | 一种生物特征成像的方法与设备 |
Family Cites Families (20)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN100433043C (zh) * | 2006-04-18 | 2008-11-12 | 南京大学 | 自动跟踪无侵害虹膜图像采集装置 |
JP2008052123A (ja) * | 2006-08-25 | 2008-03-06 | Eastman Kodak Co | 撮像装置 |
CN100524343C (zh) * | 2007-03-13 | 2009-08-05 | 杭州电子科技大学 | 双眼虹膜的采集方法和装置 |
CN101116609B (zh) * | 2007-08-30 | 2010-06-16 | 中国科学技术大学 | 扫描式自动变焦虹膜图像采集系统及采集方法 |
JP2009063942A (ja) * | 2007-09-10 | 2009-03-26 | Sumitomo Electric Ind Ltd | 遠赤外線カメラ用レンズ、レンズユニット及び撮像装置 |
JP4544282B2 (ja) * | 2007-09-14 | 2010-09-15 | ソニー株式会社 | データ処理装置、およびデータ処理方法、並びにプログラム |
WO2009043047A1 (en) * | 2007-09-28 | 2009-04-02 | Eye Controls, Llc | Systems and methods for biometric identification |
JP5173694B2 (ja) * | 2008-09-19 | 2013-04-03 | ペンタックスリコーイメージング株式会社 | デジタルカメラ |
US8317325B2 (en) * | 2008-10-31 | 2012-11-27 | Cross Match Technologies, Inc. | Apparatus and method for two eye imaging for iris identification |
CN101877061A (zh) * | 2009-04-30 | 2010-11-03 | 宫雅卓 | 基于单摄像头的双眼虹膜图像采集方法及装置 |
CN102648624B (zh) * | 2009-12-07 | 2016-04-13 | 诺基亚技术有限公司 | 用于自动聚焦的设备、方法 |
CN101770573B (zh) * | 2010-01-14 | 2012-02-01 | 沈洪泉 | 用于虹膜识别的自动聚焦虹膜图像成像装置及其控制方法 |
US20130089240A1 (en) * | 2011-10-07 | 2013-04-11 | Aoptix Technologies, Inc. | Handheld iris imager |
US8723798B2 (en) * | 2011-10-21 | 2014-05-13 | Matthew T. Vernacchia | Systems and methods for obtaining user command from gaze direction |
CN102622586A (zh) * | 2012-03-08 | 2012-08-01 | 湖南创远智能科技有限公司 | 一种利用可见光辅助调焦的虹膜采集光学系统 |
CN102708357A (zh) * | 2012-04-12 | 2012-10-03 | 北京释码大华科技有限公司 | 单图像传感器双眼虹膜识别设备 |
US9398264B2 (en) * | 2012-10-19 | 2016-07-19 | Qualcomm Incorporated | Multi-camera system using folded optics |
CN103020612A (zh) * | 2013-01-05 | 2013-04-03 | 南京航空航天大学 | 一种虹膜图像采集装置及方法 |
CN103099624A (zh) * | 2013-01-11 | 2013-05-15 | 北京释码大华科技有限公司 | 虹膜测距板、虹膜识别一体机及使用其的虹膜识别方法 |
CN103106401B (zh) * | 2013-02-06 | 2017-02-22 | 北京中科虹霸科技有限公司 | 一种具有人机交互机制的移动终端虹膜识别装置 |
-
2013
- 2013-10-21 CN CN201310494298.1A patent/CN103593647A/zh active Pending
- 2013-10-21 CN CN201910418663.8A patent/CN110135367A/zh active Pending
-
2014
- 2014-03-26 US US14/648,368 patent/US9852338B2/en active Active
- 2014-03-26 EP EP14856525.2A patent/EP2924608A4/en not_active Withdrawn
- 2014-03-26 WO PCT/CN2014/000330 patent/WO2015058460A1/zh active Application Filing
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1464323A (zh) * | 2002-06-13 | 2003-12-31 | 北京中星微电子有限公司 | 自动对焦技术 |
CN102855476A (zh) | 2011-06-27 | 2013-01-02 | 王晓鹏 | 单图像传感器自适应双眼虹膜同步采集系统 |
CN103136421A (zh) * | 2013-01-31 | 2013-06-05 | 沈洪泉 | 用于虹膜成像装置的系统级光电优化设计方法 |
CN103593647A (zh) * | 2013-10-21 | 2014-02-19 | 王晓鹏 | 一种生物特征成像的方法与设备 |
Non-Patent Citations (1)
Title |
---|
See also references of EP2924608A4 |
Also Published As
Publication number | Publication date |
---|---|
CN110135367A (zh) | 2019-08-16 |
US9852338B2 (en) | 2017-12-26 |
CN103593647A (zh) | 2014-02-19 |
EP2924608A1 (en) | 2015-09-30 |
US20150310272A1 (en) | 2015-10-29 |
EP2924608A4 (en) | 2016-11-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2015058460A1 (zh) | 一种生物特征成像的方法与设备 | |
US9690970B2 (en) | Method and device for mobile terminal biometric feature imaging | |
CN103986876B (zh) | 一种图像获取终端和图像获取方法 | |
WO2017031948A1 (zh) | 成像装置和成像方法 | |
CN105473057B (zh) | 用于虹膜成像的优化成像装置 | |
CN106507087B (zh) | 一种终端成像方法及系统 | |
JP5368723B2 (ja) | 撮像装置及びその制御方法 | |
WO2015113479A1 (zh) | 一种具有人机交互机制的移动终端虹膜识别装置和方法 | |
WO2020078440A1 (zh) | 采集高清晰度面部图像的装置和摄像头云台自动俯仰调节的方法 | |
WO2015180509A1 (zh) | 一种图像获取终端和图像获取方法 | |
Venugopalan et al. | Long range iris acquisition system for stationary and mobile subjects | |
US20140368695A1 (en) | Control device and storage medium | |
JP5991755B2 (ja) | 自動焦点検出装置およびその制御方法 | |
US11947717B2 (en) | Gaze estimation systems and methods using relative points of regard | |
JP2015005799A (ja) | 被写体検出装置およびその制御方法、撮像装置、被写体検出装置の制御プログラムおよび記憶媒体 | |
CN112782854B (zh) | 头戴式显示设备以及距离测量器 | |
US8295605B2 (en) | Method for identifying dimensions of shot subject | |
CN106595489A (zh) | 一种实时测距的移动终端及方法 | |
WO2018019011A1 (zh) | 微距拍摄处理方法、装置和终端设备 | |
CN106060366B (zh) | 图像对焦系统、拍摄装置和电子设备 | |
Lee et al. | Auto-focusing method for remote gaze tracking camera | |
WO2018019020A1 (zh) | 控制方法、装置及移动终端 | |
Zhang et al. | Light field photography for iris image acquisition | |
TW201236448A (en) | Auto-focusing camera and method for automatically focusing of the camera | |
JP2005287878A (ja) | 生体判別装置および認証装置ならびに生体判別方法 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
WWE | Wipo information: entry into national phase |
Ref document number: 14648368 Country of ref document: US |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 14856525 Country of ref document: EP Kind code of ref document: A1 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2014856525 Country of ref document: EP |
|
NENP | Non-entry into the national phase |
Ref country code: DE |