JP2007018248A - Image processor, image processing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To propose an image processor, an image processing method and a program which can achieve speeding up. <P>SOLUTION: The image processor is provided with a detection means which detects a pixel which takes a local minimum for every pixel string corresponding to a scanning direction for images acquired as an imaging result of identification target comprising a living body. Consequently, since the identification target of a living body expressed in image can be grasped from the relation of mutual adjoining pixels in a pixel string, identification target of a living body can be extracted by scanning of a pixel string, without having to perform complicated functional operations. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an image processing method, and a program, and is suitable for application to biometric authentication.

  Conventionally, many authentication apparatuses that use biometric fingerprints as targets for biometric authentication have been proposed, but in recent years, blood vessels in the living body have attracted attention as one of targets for biometric authentication.

Specifically, a blood vessel is extracted by performing an edge extraction process on image data obtained as a blood vessel imaging result, and a line passing through the center of the blood vessel is detected by executing a linearization process called morphology. An apparatus configured as described above has been proposed (see, for example, Patent Document 1).
JP 2001-70247 A

  By the way, in such linearization processing, there is a problem in that the speed is reduced as a result of requiring a complicated function operation for each processing unit.

  The present invention has been made in consideration of the above points, and intends to propose an image processing apparatus, an image processing method, and a program which can be speeded up.

  In order to solve such a problem, the present invention is an image processing apparatus that detects, from an image obtained as an imaging result of an identification target in a living body, a pixel having an extreme value for each pixel column corresponding to a scanning direction. Means were provided.

  Therefore, in this image processing apparatus, since the identification target of the living body represented in the image can be grasped from the relationship between adjacent pixels in the pixel array, the identification target of the living body is detected by scanning the pixel array without performing complicated function calculation. Can be extracted.

  The present invention is also an image processing method, comprising: a first step of measuring a pixel value for each pixel column corresponding to a scanning direction for an image obtained as an imaging result of an identification target in a living body; Based on the pixel value measured for each corresponding pixel column, a second step of detecting a pixel having an extreme value for each pixel column is provided.

  Therefore, in this image processing method, since the identification object of the living body represented in the image can be grasped from the relationship between adjacent pixels in the pixel array, the identification object of the living body is extracted by scanning the pixel array without performing a complicated function calculation. can do.

  Furthermore, the present invention provides a program for a computer responsible for controlling an apparatus that processes an image obtained as an imaging result of an identification target in a living body, for each pixel column corresponding to the scanning direction. A process for detecting a pixel that takes a value was executed.

  Therefore, in this program, since the identification target of the living body represented in the image can be grasped from the relationship between adjacent pixels in the pixel array, the identification target of the living body is extracted by scanning the pixel array without performing a complicated function calculation. Can do.

  According to the present invention, for an image obtained as an imaging result of an identification target in a living body, pixels that take extreme values are detected from a predetermined direction in units of pixel columns. From this relationship, the identification target of the living body represented in the image can be grasped, so that the identification target of the living body can be extracted by scanning the pixel row without performing a complicated function calculation, and thus the image processing apparatus and image that can be speeded up A processing method and a program can be realized.

  Hereinafter, embodiments to which the present invention is applied will be described in detail with reference to the drawings.

(1) Configuration of Biological Information Generating Device In FIG. 1, reference numeral 1 denotes the biometric information generating device 1 according to the present embodiment as a whole. An information generation unit 3 that generates data for identifying a living body (hereinafter referred to as biological identification data) is connected to each other via a cable.

(2) Configuration of Blood Vessel Imaging Unit This blood vessel imaging unit 2 has a curved guide groove 11 formed so as to imitate a finger FG at a predetermined position of the housing 1A of the biological information generating device 1, and the guide An imaging opening 12 is disposed on the bottom surface of the groove 11.

  A colorless and transparent opening cover portion 13 made of a predetermined material is provided on the surface of the imaging opening portion 12, while a camera portion 14 is disposed immediately below the imaging opening portion 12 inside the housing 1A. .

  Further, on the side surface of the guide groove 11, a pair of near-infrared light sources 15 (15 </ b> A and 15 </ b> B) that irradiate near-infrared light specifically absorbed with respect to hemoglobin as imaging light for blood vessels are provided on the guide groove 11. Is arranged so as to sandwich the imaging opening 12 in parallel with the short direction of the finger, and can be irradiated with near-infrared light on the finger pad side portion of the finger FG in contact with the guide groove 11. .

  Therefore, in this blood vessel imaging unit 2, the ratio of near-infrared light reflected on the surface of the finger FG is remarkably suppressed as compared with the case where near-infrared light is irradiated on the finger pad base of the finger FG. Near-infrared light incident on the inside of the finger FG via the finger FG is absorbed by hemoglobin passing through the blood vessel and scattered in tissues other than the blood vessel through the inner side of the finger FG and from the finger FG. As near-infrared light for projecting blood vessels (hereinafter referred to as blood vessel projection light), the light enters the camera unit 14 via the imaging opening 12 and the opening cover 13 in sequence.

  In the camera unit 14, the macro lens 16 and near-red light that transmits only near-infrared light in a wavelength range (approximately 900 [nm] to 1000 [nm]) that depends on both oxygenation and deoxygenation hemoglobin. An external light transmission filter 17 and a CCD image sensor 18 are sequentially arranged, and blood vessel projection light incident from the opening cover 13 is sequentially passed through the macro lens 16 and the near-infrared light transmission filter 17 to the CCD image sensor 18. To the imaging surface. Thus, the camera unit 14 can faithfully image both venous and arterial capillaries mixed inside the adjacent finger FG.

  Under the control of the information generation unit 3, the CCD imaging device 18 images a blood vessel or the like that is imaged on the imaging surface, and outputs the imaging result to the information generation unit 3 as an image signal.

  In this way, the blood vessel imaging unit 2 is capable of imaging blood vessels existing in the finger of the living body.

(3) Configuration of Information Generation Unit On the other hand, the information generation unit 3 is configured by connecting a blood vessel imaging drive unit 21 and an image processing unit 22 to the control unit 20 as shown in FIG. ing.

The control unit 20 is a CPU (Central Control Unit) that controls the entire biological information generating apparatus 1.
Processing unit), ROM (Read Only Memory) in which various programs are stored, and RAM (Random Access Memory) as work memory of the CPU. Given.

  When the blood vessel extraction command COM for extracting a blood vessel is given from the operation unit (not shown), the control unit 20 sets the operation mode to the blood vessel extraction mode based on the corresponding program stored in the ROM. Then, the blood vessel imaging driving unit 21 and the image processing unit 22 are controlled.

  In this case, the blood vessel imaging drive unit 21 activates the blood vessel imaging unit 2 so as to drive the near-infrared light source 15 and the CCD imaging device 18 of the camera unit 14 respectively. As a result, in the blood vessel imaging unit 2, near infrared light is irradiated from the near infrared light source 15 onto the finger pad side of the imager's finger FG (FIG. 1) that is in contact with the guide groove 11 (FIG. 1) at this time. Then, the blood vessel projection light guided to the imaging surface of the CCD image sensor 18 via the finger FG (FIG. 1) is output from the CCD image sensor 18 to the image processing unit 22 as a blood vessel projection image signal S1.

  As shown in FIG. 3, the image processing unit 22 includes an A / D (Analog / Digital) conversion unit 31, a smoothing processing unit 32, and a center line detection unit 33, and is supplied from the CCD image sensor 18. The blood vessel projection image signal S 1 is input to the A / D conversion unit 31.

  The A / D conversion unit 31 performs A / D conversion processing on the blood vessel projection image signal S1 and sends the blood vessel projection image data D1 obtained as a result to the smoothing processing unit 32.

  The smoothing processing unit 32 performs a smoothing process on the blood vessel projection image data D1 in a predetermined order with a predetermined pixel in the image as a target pixel. Specifically, as shown in FIG. 4, the smoothing processing unit 32 calculates the average luminance value of the pixel group within the fixed range FAR centered on the pixel of interest NP in the image IM.

  Here, the luminance average value of this pixel group indicates that the higher the value, the relatively less noise component in the fixed range FAR. For this reason, it is possible to specify a pixel corresponding to a blood vessel only by looking at a relatively close range around the pixel of interest NP. On the other hand, the lower the average luminance value of the pixel group, the smaller the noise component in the fixed range FAR. For this reason, it is difficult to specify a pixel corresponding to a blood vessel only by looking at a relatively close range around the pixel of interest NP.

  Accordingly, when the smoothing processing unit 32 obtains the luminance average value that is less than the threshold value set in advance as the reference in the fixed range FAR, the first smoothing target range STAR1 centered on the NP target pixel and The second smoothing target range STAR2 is selected from the second smoothing target range STAR2 that is larger than the first smoothing target range STAR1, and the luminance value of the target pixel NP is selected as the second smoothing target. Replace with the luminance average value of the pixel group in the range STAR2.

  On the other hand, the smoothing processing unit 32 selects the first smoothing target range STAR1 smaller than the second smoothing target range STAR2 when the luminance average value that is equal to or higher than the battle value is obtained in the fixed range FAR. Then, the luminance value of the target pixel NP is replaced with the average luminance value of the pixel group in the first smoothing target range STAR1.

  In this way, the smoothing processing unit 32 switches the size of the smoothing target range STAR according to the luminance around the pixel for each predetermined target pixel NP in the image IM, and sets the luminance value of the target pixel NP. Then, it replaces with the luminance average value of the pixel group in the smoothing target range STAR, and the centered line detection unit 33 uses the replaced image as data (hereinafter referred to as smoothed blood vessel projection image data) D2 (FIG. 3). It is made to send out.

  As a result, the smoothing processing unit 32 can remove the noise component included in the image IM so as to be scattered.

The center line detection unit 33 detects a pixel having a minimum value (hereinafter referred to as a minimum pixel) for each pixel column corresponding to the scanning direction in the image of the smoothed blood vessel projection image data D2. In the case of this embodiment, as shown in FIG. 5A, the center line detection unit 33 performs the pixel column for each pixel column HPL ₁ , HPL ₂ ,..., HPL _n corresponding to the horizontal scanning direction. The minimum pixel is detected by measuring the luminance value of each pixel (hereinafter referred to as a line pixel group).

Further, as shown in FIG. 5B, the center line detection unit 33 performs, for each pixel column PPL ₁ , PPL ₂ ,..., PPL _n corresponding to, for example, a vertical scanning direction different from the horizontal scanning direction. The minimum pixel is detected by measuring the luminance value of each pixel in the pixel column (hereinafter referred to as a line pixel group).

  Here, for example, as shown in FIG. 6, the center of the blood vessel BL in the image IM of the smoothed blood vessel projection image data D2 is the minimum point of the luminance value on the scanning line. That is, the minimum pixels MP1 and MP2 of the line pixel group in a certain pixel column HPL represent the center position of the blood vessel BL intersecting with the pixel column HPL.

  However, when detecting a minimum pixel for each pixel row HPL in the horizontal scanning direction, all the pixels originally corresponding to the center of the blood vessel portion BLp are minimum for the blood vessel portion BLp facing the same horizontal direction as the scanning direction. Although it should be detected as a pixel, in reality, only one pixel out of all the pixels is detected as a minimal pixel MP1 (hereinafter referred to as a minimal pixel missing state). become. In addition, when detecting a minimum pixel for each pixel row HPL in the vertical scanning direction, a minimum pixel missing state is similarly generated in a blood vessel portion (not shown) in the same vertical direction as the scanning direction. Become.

Therefore, the center line detection unit 33 uses a set of minimal pixels in the pixel rows HPL _{1 to} HPL _n in the horizontal scanning direction obtained as a detection result as a unit, while the pixel rows PPL ₁ to PPL _{1 in} the vertical scanning direction. A set of minimum pixels in PPL _n is used as a unit, these sets are combined by logical sum, and data of the minimum pixels combined by the logical sum is sent to the control unit 20 as biometric identification data D3.

  As a result, the center line detection unit 33 can supplement the missing pixel as the minimum pixel in the pixel rows HPL and PPL in the scanning direction, and as a result, the minimum pixel missing state can be prevented in advance. .

  When the control unit 20 receives the biometric identification data D3 from the image processing unit 22, the control unit 20 registers the identification data D3 as registration data in a recording medium (not shown) provided inside or outside, or exchanges the registration data with the registration data. The data is sent to a collator (not shown) provided inside or outside as a comparison target, and the control for the blood vessel imaging drive unit 21 and the image processing unit 22 is released.

  In this way, the information generating unit 3 can generate biometric identification data for identifying a biometric from the imaging result.

(4) Operation and Effect In the above configuration, the biological information generating apparatus 1 uses the pixel array HPL (FIG. 5A) and PPL corresponding to the scanning direction for an image obtained as an imaging result of blood vessels inherent in the living body. For each (FIG. 5B), a minimum pixel is detected.

  Therefore, in this biological information generating apparatus 1, since the center position of the blood vessel represented in the image can be grasped from the relationship between adjacent pixels in the pixel row, the pixel row HPL can be performed without performing a complicated filter operation such as morphology, for example. The center line representing the blood vessel formation pattern can be extracted only by PPL scanning, and thus the speed can be increased.

The biological information generating apparatus 1 also includes pixel columns HPL _{1 to} HPL _n corresponding to the first scanning direction (horizontal scanning direction) and pixel column PPL ₁ corresponding to the second scanning direction (vertical scanning direction). ˜PPL _n are respectively detected, and the tiny pixels in the pixel columns HPL _{1 to} HPL _{n and} the tiny pixels in the pixel rows PPL _{1 to} PPL _n are combined by OR.

  Therefore, in this biometric information generation device 1, as described above with reference to FIG. 6, it is possible to supplement the missing pixels as the minimum pixels in the pixel rows HPL and PPL in the scanning direction, so that the blood vessel formation pattern is more accurately performed. A center line representing can be extracted. As shown in FIG. 7, this is because an image (FIG. 7A) obtained by taking the logical sum of the minimum pixels of each pixel row corresponding to two scanning directions and a pixel corresponding to one scanning direction. It is also apparent from a visual comparison with the image (FIG. 7B) obtained when the minimum pixels in the column are taken.

  Further, the biometric information generation device 1 smoothes an image obtained as a blood vessel imaging result before detecting such a minimum pixel. Therefore, in this biological information generating apparatus 1, since it is possible to avoid detecting pixels corresponding to noise as minimal pixels, it is possible to accurately extract a center line representing a blood vessel formation pattern.

  Further, the biometric information generation device 1 switches the size of the smoothing target range STAR according to a global change around the destination pixel NP (FIG. 4) as the smoothing process, and changes the luminance value of the destination pixel NP. A method of replacing the luminance average value of the pixel group in the switched smoothing target range STAR is adopted.

  Therefore, in this biometric information generation device 1, it is possible to avoid performing sort processing for detecting intermediate values for each processing unit, compared to the case where smoothing processing called median is employed. Higher speed can be achieved.

  Actually, as a specific switching method of the size in the smoothing target range STAR, the biological information generating apparatus 1 has an average luminance value of the pixel group in the fixed range FAR centered on the destination pixel NP (FIG. 4). When the threshold value is less than the threshold value, the second smoothing target range STAR2 that is larger than the first smoothing target range STAR1 is switched to, and when the threshold value is equal to or higher than the threshold value, the second smoothing target range STAR2 is exceeded. Switch to the smaller first smoothing target range STAR1.

  Therefore, in this biometric information generation device 1, as shown in FIG. 8A, the bright part can expose the blood vessel without damaging the detail of the blood vessel, and the dark part is not affected by noise. In addition, when smoothing is performed under a single smoothing target range without switching the size of the smoothing target range STAR, the blood vessel is affected by noise in a dark portion under a condition where the kernel size is small. It cannot be expressed (FIG. 8 (B)), and under the condition where the kernel size is large, the detail of the blood vessel is impaired in the bright part (FIG. 8 (C)), and the size of the smoothing target range STAR is set. It can be seen that the difference is clear even when visually compared with the case of switching (FIG. 8A).

  According to the above configuration, since an extremely small pixel is detected for each pixel column corresponding to the scanning direction in an image obtained as a result of imaging a blood vessel existing in the living body, the relationship between adjacent pixels in the pixel column is detected. From this, the center position of the blood vessel represented in the image can be grasped, so that the center line representing the blood vessel formation pattern can be extracted only by scanning the pixel row without performing a complicated filter operation such as morphology. The biological information generating apparatus 1 that can be speeded up can be realized.

(5) Other Embodiments In the above-described embodiment, the case where a blood vessel inherent in a living body is applied as an identification target has been described. However, the present invention is not limited to this, and paper called a pattern is used. Such a pattern, a fingerprint that appears in the living body, an ear or a face, or a nerve that is inherent in the living body may be applied. In short, the identification target can be selected adaptively according to its application. By the way, when a nerve is an authentication target, for example, if a marker specific to the nerve is injected into the body and the marker is imaged, the nerve is an identification target in the same manner as in the above-described embodiment. be able to. Of the identification objects, if the net-shaped identification objects such as patterns, blood vessels, and fingerprints are applied, the effects of the present invention are remarkably exhibited.

  In addition, as a range of the identification target, a finger that is a part of a living body part is applied. Alternatively, the whole living body may be applied. Even if the identification target is not a living body, the whole or a part of the identification target can be set as a range.

  Further, as the imaging means for imaging the identification target, the configuration shown in FIG. 1 is applied. However, the present invention is not limited to this, and various configurations are possible depending on the application, type of identification target, and the like. Can be widely applied.

  In the above-described embodiment, two scanning directions (horizontal scanning direction and vertical scanning direction) are used as detection means for detecting a pixel having an extreme value for each pixel column corresponding to the scanning direction in the captured image. Although the case where the minimum pixel is detected for each pixel column corresponding to the above has been described, the present invention is not limited to this, and the minimum pixel may be detected for each pixel column corresponding to one scanning direction. You may make it detect a minimum pixel for every pixel row corresponding to three or more scanning directions.

  Further, the horizontal scanning direction and the vertical scanning direction are applied as the scanning directions. However, the present invention is not limited to this, and any scanning direction of 360 [°] centering on the image is applicable. You can choose. For example, when a blood vessel or a fingerprint having a living body part as a finger is an identification target, the pointing direction of the living body part (finger) imaged on the CCD image sensor 18 and the longitudinal direction opposite to the pointing direction are less than an obtuse angle. The center line representing the formation pattern of blood vessels that run mainly in the longitudinal direction can be extracted with higher accuracy by selecting a direction that forms an angle of λ, more preferably 45 [°] or 135 [°], or a direction that forms an angle before and after that. it can.

  Further, although the luminance value is applied as the detection index of the minimum pixel, the present invention is not limited to this, and various other pixel values such as a color difference value can be used as the detection index. Note that depending on the imaging method and the type of identification target, the pixel corresponding to the identification target in the captured image may be black and the other pixels corresponding to the background may be white. In this case, the maximum value is obtained. Pixels can be detected.

  Further, in the above-described embodiment, as the smoothing means for smoothing the image, the smoothing target range STAR1 or STAR2 is selected according to the luminance average value of the pixel group in the fixed range FAR, and the destination pixel NP (FIG. 4) is selected. ) Is replaced with the average luminance value of the pixel group in the selected smoothing target range STAR. However, the present invention is not limited to this, and the fixed range FAR and / or the smoothing target range. The average luminance value in the STAR may be changed to, for example, an intermediate luminance value or a minimum luminance value. Even if it does in this way, the effect similar to the above-mentioned embodiment can be acquired.

  Further, as an index for switching the size of the smoothing target range STAR, a luminance average value in a state where the target pixel NP is excluded from the pixel group in the fixed range FAR may be employed. By doing this, it is possible to avoid erroneous selection of the smoothing target range STAR due to the pixel of interest NP itself being noise, and thus it is possible to more appropriately identify pixels corresponding to blood vessels. .

  Furthermore, instead of the smoothing means of the above-described embodiment, a generally commonly used smoothing means such as a median filter may be applied.

Further, in the above-described embodiment, the first scanning is performed as a combination means for combining a set of pixels having the minimum value detected in each pixel column corresponding to the same scanning direction as a unit and combining the sets based on the unit. The minimum pixels of the pixel columns HPL _{1 to} HPL _n corresponding to the direction (horizontal scanning direction) and the minimum pixels of the pixel columns PPL _{1 to} PPL _n corresponding to the second scanning direction (vertical scanning direction) are logically calculated. Although the case of combining by sum has been described, the present invention is not limited to this, and can be combined according to various combination rules, such as determining whether or not the minimum pixels are added together with the luminance value.

  Furthermore, in the above-described embodiment, the case where the image processing unit 22 is operated in hardware has been described. However, the present invention is not limited to this, and the smoothing processing unit 32 and the center line in the image processing unit 22 are not limited thereto. You may make it operate | move like software with the program which performs the various processes of the detection part 33. FIG.

  The present invention can be used in a field using a technique for identifying a living body.

It is a basic diagram which shows the whole structure of the biometric information generation apparatus by this Embodiment. It is a block diagram which shows the structure of an information generation part. It is a block diagram which shows the structure of an image process part. It is a basic diagram with which it uses for description of switching of the smoothing object range. It is an approximate line figure used for explanation of detection of a minimum pixel. It is a basic diagram with which it uses for description of the relationship between a minimum pixel and the center position of the blood vessel. It is a basic diagram which shows the image of a smoothing process result. It is a basic diagram which shows the image of a centerline detection process result.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Living body information generation apparatus, 2 ... Blood vessel imaging part, 3 ... Information generation part, 14 ... Camera part, 15A, 15B ... Near infrared light source, 16 ... Macro lens, 17 ... Near red External light transmission filter, 18 ... CCD image sensor, 20 ... control unit, 21 ... blood vessel imaging drive unit, 22 ... image processing unit, 31 ... A / D conversion unit, 32 ... smoothing processing unit, 33... Centerline detection unit, COM... Command, S1... Blood vessel projection image signal, D1... Blood vessel projection image data, D2 ... smoothed blood vessel projection image data, D3. Region, STAR1, STAR2 ... smoothing target region, NP ... pixel of interest, pixel column ... HPL, PPL, MP1, MP2 ... local minimum.

Claims (9)

An image processing apparatus comprising: a detection unit configured to detect a pixel having an extreme value for each pixel row corresponding to a scanning direction of an image obtained as an imaging result of an identification target. A smoothing means for smoothing an image obtained as an imaging result of the identification target in a living body;
The detecting means is
2. The image processing apparatus according to claim 1, wherein, in the image smoothed by the smoothing unit, a pixel having an extreme value is detected for each pixel row corresponding to a scanning direction. The detecting means is
For each pixel column corresponding to a plurality of scanning directions, a pixel having the above extreme value is detected,
The apparatus further comprises a combination means for combining a set of pixels having the extreme value detected in each pixel row corresponding to the same scanning direction as a unit and combining the sets with the unit. The image processing apparatus according to 1. The union means
The image processing apparatus according to claim 1, wherein the sets are combined by logical sum. The image processing apparatus according to claim 1, wherein the identification target is an identification target in a living body. The image processing apparatus according to claim 1, wherein the identification target is a net-like identification target. The image processing apparatus according to claim 1, wherein the direction is a direction that forms 45 [°] or 135 [°] with the longitudinal direction of the living body imaged on the image sensor, or a front and rear thereof. A first step of measuring a pixel value for each pixel column corresponding to a scanning direction for an image obtained as an imaging result of an identification target in a living body;
And a second step of detecting a pixel having an extreme value for each pixel row based on the pixel value measured for each pixel row corresponding to the scanning direction. For a computer responsible for controlling an apparatus that processes an image obtained as an imaging result of an identification target in a living body,
A program for executing a process for detecting a pixel having an extreme value for each pixel row corresponding to a scanning direction for the image.