JP2005032067A - Biological body image acquisition apparatus, biological authentication system and biological body image acquisition method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a biological body image acquisition apparatus with wide dynamic range and high accuracy according to a varied state of an environment conditions such as external light, object shape and permeability. <P>SOLUTION: In the image acquisition apparatus acquiring image information for biometrics, the image acquisition apparatus includes an imaging means; a concentration conversion means for concentration-converting and outputting the output of above imaging means, based on a concentration conversion curve; a detecting means of a biological information luminance range for discriminating the area, including the biological information and detecting the luminance distribution; and a control means for controlling the concentration conversion means so that, in the concentration conversion curve, the ratio of the number of luminance levels in above biological information area becomes greater than the ratio of the number of the levels outside the biological information area. The discrimination of the area, including the biological information, is based on either by obtaining a frequency distribution of the image information, the spatial frequency being higher than a constant level, or by comparing the luminance distribution of the image information with that obtained at the time of external incident light, the dispersion being greater than a constant level. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an image acquisition device and an image acquisition method, and more particularly, to a biometric image acquisition device and a biometric image acquisition method that are suitably mounted in a biometric authentication system such as fingerprint authentication.

  A biometric authentication system using fingerprints, faces, irises, palm prints, etc. acquires a biometric image from an image acquisition device, extracts features from the acquired image, and collates with registered data based on that information. And authenticate the identity.

  Here, as a detection method of the image acquisition apparatus, there are an optical method using a CCD or a CMOS sensor, a capacitance method, a pressure detection method, a thermal method, an electric field detection method, and the like. As another classification, a type in which subject images are collectively acquired using a two-dimensional area sensor and a one-dimensional sensor or a strip-shaped two-dimensional sensor having about 5 to 20 pixels in the sub-scanning direction are used. Thus, there is a type in which an entire image is acquired by combining images obtained by sequentially capturing an object in the sub-scanning direction.

  In the biometric authentication system, after various image processing such as contrast improvement and edge enhancement is performed on an image acquired from an image acquisition device, feature extraction processing for performing collation is performed.

Conventionally, contrast improvement processing in a biometric authentication system is performed by adjusting input of display image density by manual key operation, as introduced in the finger / palm-printing device of Patent Document 1 below, As introduced in the background deletion and binarization processing method of the line figure image of Patent Document 2, the calculation processing is performed later on the image acquired by the image acquisition device.
Japanese Patent Application Laid-Open No. 08-272953 Japanese Patent Laid-Open No. 01-1558577

  However, in contrast improvement processing in a conventional biometric authentication system, since contrast conversion processing is performed as a post-processing for manual image adjustment or acquired image data, the contrast is increased when the external light change is large. There was a problem that could not be improved sufficiently.

  For example, the luminance level changes greatly due to changes in external light due to environmental conditions such as indoors and outdoors, daytime and nighttime, and differences in finger size and transmittance due to individual differences. In particular, when mounted on a mobile phone, a PDA, or the like, such a change in external light becomes large. In such a case, even if you try to process the acquired image in post-processing, the density gradation data has already been lost in the saturated area of the acquired image or the area that has been blacked out. The density difference cannot be restored from the acquired image.

  If an optimum condition is manually set, the adjustment work becomes complicated and the burden on the user increases. Therefore, a configuration in which the exposure conditions are controlled again by taking multiple images by AE (automatic exposure correction function) can be considered. However, if the acquired data is saturated or collapsed, there is no indication of how much the exposure conditions should be changed, so the data acquisition must be repeated several times until the correct exposure is achieved. , It takes time to converge.

  Furthermore, converting the density of the acquired image data by image processing indicates that the bit accuracy is lower than that of the original image, but generally the acquired image cannot have a much larger number of bits to reduce the amount of data. Therefore, the bit accuracy after image processing becomes very low, and there is a problem that the S / N ratio is lowered.

  An object of the present invention is to provide a biometric image acquisition apparatus, a biometric authentication system, and a biometric image acquisition method with a wide dynamic range and high accuracy corresponding to environmental conditions such as external light and changes in the state of a subject such as shape and transmittance. It is to be realized.

  In order to solve the above-described problem, in an image acquisition apparatus that acquires image information for biometric authentication, a determination unit that determines a region including biometric information from an output from an imaging unit, and biometric information determined by the determination unit There is provided a biological image acquisition apparatus comprising: a control unit configured to control a ratio of the number of gradations of luminance of an area to be higher than a ratio of the number of gradations outside the biological information area.

  Further, in an image acquisition apparatus that acquires image information for biometric authentication, an imaging unit, a density conversion unit that converts and outputs an output from the imaging unit based on a density conversion curve, and an area including biometric information The biometric information luminance range detecting means for determining and detecting the luminance distribution and the density conversion curve so that the ratio of the number of gradations of the luminance of the biological information area is higher than the ratio of the number of gradations outside the biological information area. And a control means for controlling the density conversion means.

  In addition, in an image acquisition apparatus that acquires image information for biometric authentication, the imaging unit and a signal after converting the analog output of the image from the imaging unit into a digital output are converted based on a density conversion curve and output. A density conversion unit, a biometric information luminance range detection unit that detects a luminance distribution by discriminating a region including biometric information and calculates a density conversion coefficient based on the set density conversion curve, and the concentration conversion curve includes: A biological image composed of control means for controlling the density conversion means by means of the density conversion coefficient so that the ratio of the number of gradations of luminance in the biological information area is higher than the ratio of the number of gradations outside the biological information area; A biometric image acquisition device is provided that acquires the image after density conversion.

  The image acquisition apparatus for acquiring image information for biometric authentication includes an imaging unit, a differential amplifier that converts an analog output signal of the image from the imaging unit based on a density conversion curve, and biometric information. The gain and offset values of the differential amplifier are determined such that the ratio of the number of gradations of the luminance of the biological information area is higher than the ratio of the number of gradations outside the biological information area. And a biometric information luminance range detecting means for setting the density conversion curve and a control means for controlling the differential amplifier based on the calculated gain value and offset value, and obtaining a biometric image by density conversion A biological image acquisition device is provided.

  Further, in the biometric image acquisition method for acquiring image information for biometric authentication, a biometric image is captured by an imaging unit, a region including the biometric information is determined from an output from the imaging unit, and a luminance level of the biometric information region is determined. There is provided a biological image acquisition method characterized in that the ratio of the logarithm is higher than the ratio of the number of gradations outside the biological information area.

  As a result, since a wide dynamic range of the image acquisition unit can be secured, the range that can respond to environmental conditions such as outside light and changes in the shape, size, and state of the subject becomes larger, and a biological image acquisition device with high detection capability realizable.

  Even when the density conversion is not appropriate, the acquired image data includes information of a wide dynamic range, so that it is possible to shorten the convergence time until the image is acquired with appropriate density conversion.

  In addition, since image acquisition is performed while density conversion is being performed in the biological image acquisition device, it is possible to suppress a reduction in bit accuracy in preprocessing until feature extraction is performed from the acquired image.

  Furthermore, since information with a wide dynamic range can be obtained, image information in a region other than biological information can be effectively used (for example, detection of surrounding conditions such as outside light).

  According to the present invention, it is possible to provide a biological image acquisition device with a wide dynamic range and high accuracy corresponding to changes in environmental conditions such as external light, and changes in the state of a subject such as shape and transmittance. Since both high accuracy and high authentication speed can be achieved while reducing the cost and size of the imaging device, for example, there is an effect that a high-performance fingerprint authentication system in a portable terminal can be provided at low cost.

  Embodiments of the present invention will be described below with reference to the drawings.

[Embodiment 1]
FIG. 1 is a block diagram showing a schematic configuration of a fingerprint authentication device which is a biometric authentication system as Embodiment 1 of the present invention.

  The fingerprint authentication apparatus according to this embodiment includes an image acquisition unit 101 and an authentication unit 102. For example, the image acquisition unit 101 is an imaging unit having an image sensor, and the authentication unit 102 is a combination of functions executed by a personal computer, or the image acquisition unit 101 and the authentication unit 102 are one fingerprint authentication unit. And an independent device connected to a personal computer (not shown).

  In the image acquisition unit 101 in FIG. 1, reference numeral 103 denotes an LED as an illumination light source (light irradiating means), and reference numeral 104 denotes an imaging element unit including a plurality of pixels such as a CMOS type and a CCD. 105 is a timing generation unit (TG unit) that controls the image sensor unit 101 and the light source, and 106 is clamped to an appropriate DC level for processing the analog output from the image sensor unit 104 by the AD converter in the subsequent stage. This is an amplifier / clamp unit that performs amplifying. Reference numeral 107a denotes an AD converter section (ADC section), and reference numeral 108a denotes a density conversion section in the present embodiment. Reference numeral 109 denotes a communication unit to the authentication unit 102, which outputs data after density conversion of the acquired image and exchanges control signals. 110a and 110b are analog image data signal lines, and 110c and 110d are digital image data signal lines. Reference numeral 111 denotes a control line that controls each part under the control of the authentication part 102, and 112 a to 112 c are drive pulse signal lines sent from the timing generation part 105 to each part.

  Reference numeral 113 denotes a data signal line, and reference numeral 114 denotes a control signal line.

  In the authentication unit 102, 115 is a communication unit. Reference numeral 116 denotes a pre-processing unit that performs image processing such as edge enhancement in order to perform feature extraction at a later stage. Reference numeral 117 denotes a frame memory unit for performing image processing. Reference numeral 118 denotes a feature extraction unit, and reference numeral 119 denotes a registration collation unit that registers the individual features extracted in 118 in the database or compares and collates with registered data. A database unit 120 stores personal data.

  Reference numeral 121 denotes a living body detection unit that detects a living body using image information of the preprocessing unit. The living body detection is a function that is installed so as not to perform false authentication with a forged fake finger, and detects the blood flow and pulse of the finger using the image color and luminance fluctuations to determine that it is a living body. 122a is a biometric information luminance range detection unit according to the present embodiment. The biometric information luminance range detection unit 122a determines the region including the biometric information from the acquired image information, and examines the luminance distribution of the determined biometric information region. Detect the included luminance range. 123a is a control unit that controls the image acquisition unit 101 by receiving information of each unit including the biological information luminance range detection unit 122a. Reference numerals 124a to 124c denote data lines for transmitting image data. Reference numeral 125 denotes a data line and a control line between the database unit 120 and the registration / collation unit. 126 is a signal line for transmitting the extraction state of the feature extraction unit, 127 and 129a are signal lines for transmitting necessary image information to each unit, 128 is a signal line for transmitting a biological detection result, and 130a is a biological information luminance range detection result. Reference numeral 131 denotes a signal line for transmitting a signal for controlling the image acquisition unit in response to the state of each unit.

  In the present embodiment, the image output data from the image acquisition unit 101 receives the luminance range detection result of the biometric information area in the authentication unit 102, and the gradation ratio of the biometric information area is larger than the digital data after AD conversion. The density is converted so as to be output.

  FIG. 2 is a block diagram showing an internal configuration of the biological information luminance range detection unit 122a.

  In FIG. 2, reference numerals 201 and 207 schematically indicate input terminals and output terminals of the biological information luminance range detection unit 122a. An area dividing unit 202 divides the acquired image area into a plurality of areas. Here, the acquired image is divided into 8 parts each in length and breadth, and divided into 64 small regions. Reference numeral 203 denotes a spatial frequency calculation unit for each region that obtains a spatial frequency by executing Fast Fourier Transform (FFT) for each region. Reference numeral 204 denotes biological information that determines whether or not a fingerprint-specific frequency is included from the calculated spatial frequency component. An area detection unit. In the case of a fingerprint, since the pitch between ridge lines of a fingerprint is generally about 50 to 200 μm, an area where this frequency component exists is detected as a biological information area. Reference numeral 205 denotes a biological information region luminance distribution calculation unit that examines the luminance distribution from the biological information region data detected in 204. A density conversion coefficient calculation unit 206 calculates a coefficient for density conversion so that the number of gradations in the corresponding luminance range increases from the luminance distribution obtained in 205. 208a-f are data signal lines.

  FIG. 3 is a diagram schematically showing how the biological information area is detected.

  In FIG. 3A, reference numeral 301 denotes the entire acquired image, and reference numeral 302 denotes a finger image. As shown in 303a and 303b, the acquired image area is divided into 64 areas of 8 lengths and 8 widths, and the spatial frequency components of the images of the respective areas are obtained. Of the obtained spatial frequency components, an area where the frequency component of the fingerprint shows a certain ratio or more is determined as a biological information area for obtaining a luminance distribution. Here, the setting is made so that the determination is made when an area of about 80% is occupied by a fingerprint. As a result, the region 304 shown in FIG. 3B is determined to be a region having a large amount of external light component that includes only the luminance change of the low frequency component, while the region 305 has a large luminance change of the high frequency component made up of the fingerprint irregularities. It can be identified as an existing area. Accordingly, the luminance range in which the gradation ratio should be increased is obtained by obtaining the luminance distribution of the region 305.

  4 is a diagram showing input / output signals of the density converter 108a, and FIG. 5 is a diagram showing a density conversion curve of the density converter 108a.

  4A and 4B show image data at the input (a) and the output (b) of the density conversion unit 108a at the position along the straight line 306 in FIG. 3B.

Here, the input of 1024 gradations is subjected to density conversion and output in 256 gradations. X ₁ and X ₂ indicate positions on the straight line 306 in FIG. a _{1 to} b ₁ are luminance ranges detected by the biological information luminance range detection unit 122a.

As shown in FIG. 5, the density conversion of this embodiment is performed by straight lines having different slopes with respect to three input ranges of input levels 0 to a ₁ , a _{1 to} b ₁ , and b _{1 to} 1023. Is called. For such density conversion, a conversion table storing output values for input values corresponding to the number of input gradations may be prepared and conversion may be performed using a free curve. In this case, however, the circuit size occupied by the table increases. End up. Therefore, in this embodiment, as shown in FIG. 5, the circuit scale can be simplified by substituting a straight line whose inclination changes at two points. In addition, by preparing several types of preset conversion lines and switching them according to the luminance range of the input, or by determining the conversion lines by calculation when a ₁ and b ₁ are determined, the density conversion unit The circuit scale can be reduced.

When this density conversion is applied to the input data of FIG. 4A, it is converted to the output data of FIG. 4B. It can be seen that the luminance level range a _{1 to} b ₁ is converted to a _{2 to} b ₂ so that the information of the fingerprint pattern, which is biometric information, is converted so that the contrast becomes high, and the gradation ratio is high. On the other hand, other areas where the external light component is dominant are converted to low gradation ratios such as 0 to a ₂ and b _{2 to} 255. In particular, during and between b ₁ ~1023 input is 0 to A _1, modified to an appropriate value if the density conversion by giving a gray level outside the proper range without blackout or white saturation output Since it is possible to obtain a value necessary for the calculation, the time for convergence to an appropriate value can be shortened.

  Next, a biological information luminance range detection routine executed by the biological information luminance range detection unit 122a of this embodiment will be described.

  FIG. 6 is a flowchart showing a biological information luminance range detection routine executed by the biological information luminance range detection unit 122a.

In FIG. 6, when the biometric information luminance range detection routine is entered at 601, the effective image area is divided into small areas at 602. In 603, a spatial frequency is calculated for each small region. In 604, an area including 80% or more of the spatial frequency equal to or higher than the threshold value Ft (in this embodiment, the fingerprint pitch = 300 μm or less) is set as a biological information area. In 605, the luminance distribution of the biological information area determined in 604 is obtained. In 606, the biological information luminance ranges a _in and b _in are set from the luminance distribution. From the obtained biometric information luminance ranges a _in = a ₁ and b _in = b ₁ , a density conversion coefficient is obtained in 607. For example, when the luminance level range a _{1 to} b ₁ is converted into a _{2 to} b ₂ , the expression of the density conversion line in the range a _{1 to} b ₁ is obtained as y = ax + b. However _{a = (a 2 -b 2)} / (a 1 -b 1), b = (a 2 b 1 -a 1 b 2) / (a 1 -b 1). At 608, the routine ends.

  Next, an image acquisition routine executed by the authentication unit 102 of this embodiment will be described.

  FIG. 7 is a flowchart showing an image acquisition routine executed by the authentication unit 102 of this embodiment.

  When the image acquisition routine is entered in 701, the biological information luminance range detection routine described in FIG. 6 is executed on the acquired first image data in 702. In the biological information luminance range detection routine, determination is made in step 703 as to whether the density conversion coefficient is appropriate or inappropriate and needs to be changed. If the density conversion coefficient needs to be changed, in 704, a control command is issued to change the setting of the density conversion unit 108a in the image acquisition unit 101, that is, the setting of the density conversion curve, via the control unit 123a and the communication unit 115. Communicate. When the density conversion coefficient is not converted in 703, the process proceeds to 705. In 705, an image acquisition command is communicated to the image acquisition unit 101 via the control unit 123a and the communication unit 115 so as to acquire the second image data, and the routine ends in 706.

  FIG. 8 is a diagram illustrating an input signal of the density conversion unit 108a of another example.

  8 shows image data input to the density conversion unit 108a in an environment different from that in FIG. 4A at a position along the straight line 306 in FIG. 3B.

FIG. 4A is an input image when used outdoors under a clear sky, for example. The area other than the finger is saturated with external light, and the output of the finger is illuminated with both the light source and the external light. Therefore, the overall brightness is high. On the other hand, FIG. 8 shows an input image when used in a dark environment such as indoors or at night. The finger is illuminated by the light source, but the area other than the finger is not illuminated, so the luminance is low, and the output of the finger is also the light source. The overall brightness is low due to the illumination by. Therefore, biological information luminance range has a range of a ₃ ~b _3.

  FIG. 9 shows a density conversion curve in this case, and FIG. 10 shows an output signal at that time.

In FIG. 9, reference numeral 901 denotes a density conversion curve before optimization, and reference numeral 902 denotes a density conversion curve optimized after detection of the biological information luminance range. Before the density conversion coefficients are optimized for density conversion curve 901, the output biometric information brightness range for the image of a ₃ ~b ₃ in a ₄ ~b ₄ shown in FIG. 10 (a) to FIG. 9 The density is converted. As a result, it is determined that the density conversion is not optimized. On the other hand, when the input is a _{3 to} b ₃ , the density conversion curve must be switched to 902 from the point where the output is a _{4 to} b _4. Is determined. After the density conversion curve conversion, the output for the image with the biological information luminance range a _{3 to} b ₃ is converted to a _{2 to} b ₂ in FIG. 10B according to FIG. Thereby, it is possible to control so that the gradation number ratio of the concave / convex pattern information of the fingerprint becomes high with respect to the luminance distribution that varies greatly depending on conditions such as the surrounding environment, the transmittance of the subject, and the dry state.

  As described above, in this embodiment, after the signal from the imaging unit is AD-converted so that the gradation ratio of the luminance range including the biological information determined by the biological information luminance range detecting unit is increased, the 12-bit signal is converted. The biometric authentication system is characterized in that a density conversion curve is set and image acquisition is performed when gradation conversion to 8 bits is performed. Here, the frequency distribution is obtained from the first image information obtained by the imaging means, the region including the biological information is identified, the luminance range of the biological information is identified, and the luminance included in the identified biological information The second image information is obtained by controlling the density conversion means so as to increase the ratio of the number of gradations in the range.

  As a result, even if the DC component (offset) or contrast of the luminance output of the fingerprint pattern changes significantly due to environmental conditions such as external light and changes in the shape, size, and state of the subject, Since there is information of a wide dynamic range, it is possible to shorten the convergence time until acquiring an image with appropriate density conversion.

  In addition, since the image acquisition is performed while performing the density conversion in the image acquisition device, instead of performing the density conversion on the authentication device side only after the image acquisition, the bit accuracy in the preprocessing until the feature extraction from the acquired image is performed. The decrease can be suppressed.

  Furthermore, since the configuration of the present invention can obtain information of a wide dynamic range, it detects outside light other than the finger area that would normally be saturated and whitened or the low gradation side would be blacked out. be able to.

  In the present embodiment, it is only necessary to detect frequency information without performing a complicated image process for detecting a biometric information luminance range and detecting a fingerprint pattern. By performing linear approximation without using a simple conversion table, it is possible to reduce the size of the circuit, for example, by simplifying the circuit. The downsizing of the processing circuit is suitable for portable devices such as mobile phones, portable personal computers, and PDAs (personal data assistants) that require portability.

  In the present embodiment, the system for collating the subject (person) with the fingerprint of the finger has been described. However, the subject (person) is collated based on the retina of the eye, the face shape of the face, the shape and size of the hand, and the like. It can use similarly about the system which performs.

[Embodiment 2]
FIG. 11 is a block diagram showing a schematic configuration of a fingerprint authentication device which is a biometric authentication system as Embodiment 2 of the present invention.

  The fingerprint authentication apparatus according to this embodiment includes an image acquisition unit 101 and an authentication unit 102 as in the first embodiment. Here, the same numbers are assigned to the same parts as those in the first embodiment. In the present embodiment, a plurality of images are captured by sliding a finger in the sub-scanning direction with respect to a band-shaped sensor in which pixels are arranged in a line in the main scanning direction and about 10 to 20 rows are arranged in the sub-scanning direction. The case where it applies to the sweep type sensor which synthesize | combines what was obtained and acquires one fingerprint image is illustrated.

  In the image acquisition unit 101 of FIG. 11, reference numeral 103 denotes an LED as an illumination light source (light irradiating means), and 104 denotes an imaging element unit including a plurality of pixels such as a CMOS type and a CCD. Reference numeral 105 denotes a timing generation unit (TG unit) that controls the image sensor unit and the light source, and 106b denotes a clamp unit that clamps a signal from the image sensor unit 104 to a DC level suitable for processing by a subsequent circuit. Reference numeral 107b denotes an AD converter unit (ADC unit). Here, reference numeral 108b denotes a density conversion unit in the present embodiment, which controls the DC offset and the linearity while maintaining the analog output.

  Reference numeral 109 denotes a communication unit to the authentication unit 102, which outputs data after density conversion of the acquired image and exchanges control signals. 110e to 110g are analog image data signal lines, and 110h is a digital image data signal line. Reference numeral 111 denotes a control line for controlling each unit under the control of the authentication unit 102, and 112 a to 112 c are drive pulse signal lines sent from the TG unit 105 to each unit.

  122b is a biometric information luminance range detection unit according to the present embodiment. The biometric information luminance range detection unit 122b determines the region including the biometric information from the acquired image information and examines the luminance distribution of the determined biometric information region, thereby Detect the included luminance range. Reference numeral 129b denotes a digital image signal line. 130b is an output digital signal line of a detection result, and 132 is a density conversion control unit (DAC).

  Here, the density conversion unit 108 b is a differential amplifier whose gain can be variably controlled, and one of the differential inputs is connected to the analog output of the density conversion control unit 132. Upon receiving the detection result of the biological information luminance range, the density conversion control unit 132 controls the DC offset by controlling the analog potential applied to one input of the differential amplifier 108b, and the constant current source of the differential amplifier 108b. To control the gain. Thereby, density conversion is performed by controlling DC offset and linearity. Reference numeral 133 denotes one signal line for differential input, and reference numeral 134 denotes a control signal line for a constant current source.

  Reference numeral 113 denotes a data signal line, and reference numeral 114 denotes a control signal line.

  In the authentication unit 102, 115 is a communication unit.

  Reference numeral 116 denotes a pre-processing unit that performs image processing such as edge enhancement in order to perform feature extraction at a later stage. Reference numeral 117 denotes a frame memory unit 1 for performing image processing. Reference numeral 118 denotes a feature extraction unit, and reference numeral 119 denotes a registration collation unit that registers individual features extracted by the feature extraction unit 118 in a database or compares and collates with registered data. A database 120 stores personal data.

  Here, 135 is an image composition unit that acquires a single fingerprint image by connecting a plurality of images captured by sliding a finger in the sub-scanning direction, and 136 is a frame memory unit 2 for performing image processing. .

  Reference numeral 121 denotes a living body detection unit that detects a living body using image information of the preprocessing unit. The living body detection is a function that is installed so as not to perform false authentication with a forged fake finger, and detects the blood flow and pulse of the finger using the image color and luminance fluctuations to determine that it is a living body.

  123b is a control unit that receives information from each unit such as a living body detection unit and controls the image acquisition unit.

  Reference numerals 124a to 124d denote data lines for transmitting image data. Reference numeral 125 denotes a data line and a control line between the database and the registration / verification unit. 126 is a signal line for transmitting the extraction state of the feature extraction unit, 127 is a signal line for transmitting necessary image information to the living body detection unit, 128 is a signal line for transmitting a living body detection result, and 131 controls the image acquisition unit. A signal line for transmitting a signal.

  The image output data from the image acquisition unit 101 according to the present embodiment receives the luminance range detection result of the biological information area determined in the image acquisition unit 101, and the gradation of the biological information area with respect to the analog data before AD conversion. Density conversion is performed so that the ratio increases, and the result is output to the authentication unit 102.

  FIG. 12 is a block diagram illustrating an internal configuration of the biological information luminance range detection unit 122b.

  In FIG. 12, 1201 and 1207 schematically show input terminals and output terminals of the biological information luminance range detection unit 122b. Reference numeral 1202 denotes a central region cutout unit that acquires a central region in the main scanning direction from the acquired image region. Reference numeral 1203 denotes an external light discriminating unit that compares with the previous luminance and discriminates when the finger is not placed = when the external light is being input and when the finger is placed on the sensor. Reference numeral 1204 denotes a biological information region detection unit that detects that the image cut out by the central region cutout unit 1202 from the external light determination result is a biological image when a finger is placed. Reference numeral 1205 denotes a biological information region luminance distribution calculation unit that examines the luminance distribution from the biological information region data detected in 1204. A density conversion curve setting unit 1206 calculates a gain value and an offset value of a differential amplifier that performs density conversion from the luminance distribution obtained in 1205 so that the number of gradations in the corresponding luminance range increases. 1208a to 1208f are data signal lines.

  FIG. 13 is a diagram showing input / output signals of the density converter 108b, and FIG. 14 is a diagram showing a density conversion curve of the density converter 108b.

  13A and 13B show analog image data at the input (a) and the output (b) of the density conversion unit 108b.

Here, the input signal from 0 to V ₁ is converted in density, converted to an output signal from 0 to V ₂ and output. X ₁ and X ₂ indicate positions in the main scanning direction in the captured image of the finger. c _{1 to} d ₁ are the luminance ranges detected by the biological information luminance range detection unit 122b, and e ₁ is the center value thereof.

The density conversion of this embodiment is performed by a curve having two inflection points that are linear at input levels c _{1 to} d ₁ , as indicated by 1401 in FIG. Since this characteristic is obtained by giving an appropriate offset and gain so that the linear region of the differential amplifier becomes c _{1 to} d ₁ , it can be realized with a simple circuit.

When this density conversion is applied to the input data of FIG. 13A, it is converted to the output data of FIG. 13B. It can be seen that the luminance level range c _{1 to} d ₁ is converted to c _{2 to} d ₂ and the fingerprint pattern information, which is biometric information, is converted so as to have a high contrast, and the gradation ratio occupied is high. On the other hand, dominant other areas outside light component gray-scale ratio as 0~c _2, d ₂ ~V ₂ is converted low.

In particular, during input and between d ₁ ~V ₁ of 0 to C _1, to an appropriate value even if the density conversion by giving a gray level outside the proper range without blackout or white saturation output Since it becomes possible to obtain a value necessary for correction by calculation, the time for convergence to an appropriate value can be shortened. For example, when the density conversion curve is 1402 in FIG. 14, the center value e ₁ of the luminance level range c _{1 to} d ₁ is converted into e ₃ and output. Originally, the luminance center value of the biological information area should be output to e _2, and the amplitude should be c _{2 to} d ₂ . For this reason, the density conversion control unit 132 obtains the gain G ₁ of the density conversion unit as follows. Further increasing the differential input only DV _1.
G ₁ = (d ₂ −c ₂ ) / (d ₁ −c ₁ ), DV ₁ = (e ₃ −e ₂ ) / G ₁
Next, a biological information luminance range detection routine executed by the biological information luminance range detection unit 122b of this embodiment will be described.

  FIG. 15 is a flowchart showing a biological information luminance range detection routine executed by the biological information luminance range detection unit 122b of this embodiment.

  In FIG. 15, when the biometric information luminance range detection routine is entered at 1501, the central area is cut out from the effective image area at 1502. In the case of this embodiment, a central region in the main scanning direction is cut out. When a finger is placed, it corresponds to the image area of the finger belly. Here, in 1503, the standard deviation of the image signal in the central region is calculated as a variation, and compared with a variation value in the case of outside light where a finger is not set, which is set in advance as a determination level. When the finger is not placed, the output is close to saturation in daylight outside the room, and there is little change, or the room is dark at night and there is almost no output. On the other hand, when a finger is placed, finger wrinkles and fingerprint patterns appear in the luminance change, and thus the luminance variation becomes larger than a certain level. Therefore, when the variation is small, the routine is terminated, whereas when the variation is large, the process proceeds to 1504, and this cutout region is determined as the biological information region. In 1505, the luminance distribution of this region is obtained. In 1506, a gain value and an offset value for controlling the differential amplifier for setting the density conversion curve are calculated from the luminance distribution. In 1507, the routine is terminated.

  Next, a density conversion unit optimization routine executed by the image acquisition unit 101 of the present embodiment will be described.

  FIG. 16 is a flowchart showing a density conversion unit optimization routine executed by the image acquisition unit 101 of the present embodiment.

  When the density conversion unit optimization routine is entered in 1601, it is determined in 1602 whether or not a density conversion curve has been set. Since this is a sweep type sensor, in order to acquire the entire image of one finger, it is necessary to acquire and combine multiple partial images. In order to prevent the luminance change due to the fingerprint pattern from becoming difficult to detect, once the density conversion curve is optimized, it is fixed. If it has been set in 1602, the routine is terminated. If no density conversion curve is set in 1603, the biological information luminance range detection routine described in FIG. 15 is executed on the previous partial image data. When the luminance range of the biological information is detected in 1604, a density conversion unit is set in 1605. That is, the density conversion curve is set using the gain value and the offset value for controlling the differential amplifier calculated in the biological information luminance range detection routine. If the luminance range of the biological information is not detected at 1604, the routine is terminated. This routine is executed every time a partial image is acquired.

  As described above, in the present embodiment, the signal from the imaging unit converts the signal from the imaging unit into the density conversion curve in the amplification unit before AD conversion so that the gradation ratio of the luminance range including the biological information determined by the biological information luminance range detection unit is high. A biometric authentication system characterized in that image acquisition is performed with the setting of. Here, by determining the luminance variation from the first partial image information obtained by the imaging means, the region including the biological information is identified, the luminance range of the biological information is identified, and the identified biological information is included. The second partial image information is acquired by controlling the density conversion means so as to increase the ratio of the number of gradations in the luminance range.

  As a result, even if the DC component (offset) or contrast of the luminance output of the fingerprint pattern changes significantly due to environmental conditions such as external light and changes in the shape, size, and state of the subject, Since there is information of a wide dynamic range, it is possible to shorten the convergence time until acquiring an image with appropriate density conversion.

  In addition, since the image acquisition is performed while performing the density conversion in the image acquisition device, instead of performing the density conversion on the authentication device side only after the image acquisition, the bit accuracy in the preprocessing until the feature extraction from the acquired image is performed. The decrease can be suppressed.

  Furthermore, since the configuration of the present invention can obtain information of a wide dynamic range, it detects outside light other than the finger area that would normally be saturated and whitened or the low gradation side would be blacked out. be able to.

  In particular, the sweep type sensor can be configured to perform density conversion to obtain an optimum value by obtaining feedback while acquiring a partial image, and therefore, among the first few partial images of the operation of tracing one finger. Since the setting can be completed, it is possible to prevent a failure to cause the user to try again to trace the finger again because the contrast or offset of the image is inappropriate, and it is possible to realize a fingerprint authentication device that is highly usable and highly accurate.

  In the present embodiment, it is only necessary to detect luminance variation information without performing a complicated image process for detecting a biometric information luminance range and detecting a fingerprint pattern. By utilizing the linearity of the differential amplifier, it is possible to reduce the size of the circuit, for example, by simplifying the circuit. The downsizing of the processing circuit is suitable for portable devices such as mobile phones, portable personal computers, and PDAs (personal data assistants) that require portability.

  In the present embodiment, the system for collating the subject (person) with the fingerprint of the finger has been described. However, the subject (person) is collated based on the retina of the eye, the face shape of the face, the shape and size of the hand, and the like. It can use similarly about the system which performs.

The block diagram which shows the typical structure of the fingerprint authentication apparatus in Embodiment 1 of this invention. The block diagram which similarly shows the internal structure of the biometric information brightness | luminance range detection part 122a. The figure which showed the mode of detection of a living body information area typically similarly The figure which similarly shows the input / output signal of the density | concentration conversion part 108a The figure which similarly shows the density conversion curve of density conversion section 108a Similarly, a flowchart showing a biological information luminance range detection routine executed by the biological information luminance range detection unit 122a. Similarly, a flowchart illustrating an image acquisition routine executed by the authentication unit 102 The figure which similarly shows the input signal of the density | concentration conversion part 108a of another example. The figure which similarly shows the density conversion curve in the case of FIG. The figure which similarly shows the output signal in the case of FIG. The block diagram which shows the typical structure of the fingerprint authentication apparatus in Embodiment 2 of this invention. The block diagram which similarly shows the internal structure of a biometric information brightness | luminance range detection part The figure which similarly shows the input / output signal of the density | concentration conversion part 108b The figure which similarly shows the density conversion curve of density conversion section 108b Similarly, a flowchart showing a biological information luminance range detection routine executed by the biological information luminance range detection unit 122b. Similarly, a flowchart illustrating a density conversion unit optimization routine executed by the image acquisition unit 101.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Image acquisition part 102 Authentication part 103 Light source 107a, 107b ADC part 108a, 108b Density conversion part 122a, 122b Biometric information brightness | luminance range detection part 123a Control part 132 Density conversion control part

Claims (11)

  In an image acquisition apparatus that acquires image information for biometric authentication, a determination unit that determines a region including biometric information from an output from an imaging unit, and a luminance gradation number of the biometric information region determined by the determination unit And a control means for controlling the ratio to be higher than the ratio of the number of gradations outside the biological information area.   In an image acquisition device that acquires image information for biometric authentication, an imaging unit, a density conversion unit that outputs the output from the imaging unit by converting the density based on a density conversion curve, and an area including biometric information are determined. The biometric information luminance range detecting means for detecting the luminance distribution and the density conversion curve so that the ratio of the number of gradations of the luminance of the biological information area is higher than the ratio of the number of gradations outside the biological information area. A biological image acquisition apparatus comprising: control means for controlling density conversion means.   The biological image acquisition apparatus according to claim 1, wherein the imaging unit is a CCD sensor or a CMOS sensor.   The living body information luminance range detecting means obtains a frequency distribution of image information, and determines that the area includes living body information when the spatial frequency is higher than a certain level. Image acquisition device.   The biological information luminance range detecting means compares the luminance distribution of the image information with that when external light is incident, and determines that the biological information includes an area when the luminance variation is larger than a certain level. Or the biological image acquisition apparatus of 3.   In an image acquisition apparatus for acquiring image information for biometric authentication, density conversion is performed by converting an image pickup unit and a signal obtained by converting an analog output of an image from the image pickup unit into a digital output based on a density conversion curve. Means for detecting a luminance distribution by discriminating a region including biometric information and calculating a density conversion coefficient based on the set density conversion curve, and the concentration conversion curve includes biometric information. And a control means for controlling the density conversion means by the density conversion coefficient so that the ratio of the number of gradations of the luminance of the region is higher than the ratio of the number of gradations outside the biological information area. A biometric image acquisition apparatus characterized by converting and acquiring.   In an image acquisition apparatus for acquiring image information for biometric authentication, an imaging unit, a differential amplifier that converts an analog output signal of the image from the imaging unit based on a density conversion curve, and an area including biometric information The luminance distribution is determined and detected, and the gain value and offset value of the differential amplifier are calculated so that the ratio of the number of gradations of the luminance in the biological information area is higher than the ratio of the number of gradations outside the biological information area. And a biometric information luminance range detecting means for setting the density conversion curve and a control means for controlling the differential amplifier based on the calculated gain value and offset value, and obtaining a biometric image by converting the density. A biological image acquisition device characterized by the above.   A biological body comprising: the image acquisition device according to claim 1; and a collation unit that collates an image signal from the image acquisition device and a biological image signal acquired in advance. Authentication system.   The biometric authentication system according to claim 8, wherein the living body is an eye, a face, a hand, or a finger.   A portable terminal comprising the biometric authentication system according to claim 8 or 9.   In a biometric image acquisition method for acquiring image information for biometric authentication, a living body is imaged by an imaging unit, a region including the biometric information is determined from an output from the imaging unit, and the number of luminance gradations of the biometric information region The biometric image acquisition method is characterized in that the ratio is higher than the ratio of the number of gradations outside the biometric information area.

Images