JP2008299678A - Personal identification apparatus and personal identification program for use in the same - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a personal identification apparatus which is simple and highly precise for a person to be identified, and to provide a personal identification program for use in the same. <P>SOLUTION: The personal identification apparatus includes a handle part with a built-in light source, a light reception part for receiving light emitted from the light source, and an information processing part for identifying a person on the basis of the light received by the light reception part. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a personal authentication technique, and more particularly to a personal authentication device and a personal authentication program used therefor, and more particularly, a device for performing personal authentication based on a blood vessel pattern of a human hand vein and a program used therefor About.

  Conventionally, knowledge that relies on memory such as passwords and PINs (Personal Identification Numbers) and articles owned by the person such as cards and seals have been used for authentication of the person. However, there are risks such as forgetting, analogy, loss, and plagiarism. Therefore, research and development and commercialization of personal authentication based on biometric information, so-called biometrics authentication, are progressing as information of the person who does not have these risks. As biometric information used for biometric authentication, fingerprints, irises, faces, veins, and the like are described in Non-Patent Documents 1 to 9, for example.

  Among these biological information, one of the safe information that is in the body and is difficult to be known by others is the vein blood vessel pattern. Biometric authentication (hereinafter referred to as “vein authentication”) using vein patterns of veins can be performed in principle without contact and is difficult to counterfeit because it uses in-vivo information that is difficult to identify with the naked eye. There are advantages. More specifically, it is said that the venous blood vessel pattern is different between twins, and it is information in the body that exists under the skin, in the epidermis, dermis, and deep in the fat layer. Thus, it is said that the information is safer because it is not easily observed from the outside by a simple means such as photographing and contact, as described above. Here, the “venous blood vessel pattern” means a complicated pattern such as a mesh woven by veins of veins.

  In vein authentication, it is common to use a thick and stable blood vessel pattern without using an unstable thin blood vessel such as a capillary blood vessel. There are two types of near-infrared irradiation methods for photographing the vein blood vessel pattern. One is a “reflective type” that irradiates near infrared rays to a site to be authenticated and captures reflected light (see Non-Patent Documents 3 to 5 below), and the other has passed through the site to be authenticated. It is a “transmission type” (see Non-Patent Document 6 below) for photographing light.

  On the other hand, palms (see Non-Patent Document 5 below), backs of hands (see Non-Patent Documents 3 and 4 below), and finger veins (see Non-Patent Document 6 below) are easy to capture vein blood vessel patterns during authentication. ) Is considered. Vein authentication using a palm has the advantage that personal identification is possible without touching the device at all (fully contactless type). This authentication operation requires only a hand over the sensor, and is highly convenient taking advantage of the goodness of the reflection type photographing method. In addition, vein authentication using a finger vein is a technique in which a near-infrared ray is transmitted mainly through a second joint portion of a finger, and a blood vessel pattern of the finger vein is photographed and authenticated. In addition, vein authentication using the vein pattern on the back of the hand is not limited, but is suitable mainly for products for entry / exit management. The hand metallurgy and the sensor mouth are closed with the back, and the back of the hand is pressed against the sensor mouth that is opened to the size of the back of the hand for authentication. In general, a micro switch is attached to the sensor port, and when the sensor port is closed with an instep, the image is taken.

X. Yuan, J .; M.M. Lu, T .; Yahagi, “A Method of Face Recognition Based on Control Map”, IEEE Trans. EIS, vol. 125, no. 3,426-434, March 2005 J. et al. M.M. Lu, X .; Yuan, T .; Yahagi, “A Method of Face Recognition Based on Futzing Clustering and Parallel Neural Networks”, Signal Processing, vol. 86, no. 8, 2026-2039, Aug. 2006. S. K. Im, H .; M.M. Park, Y .; W. Kim, S .; C. Han, S .; W. Kim and C.M. H. Hang, “An Biometric Identification System by Extraction Hand Vein Patterns”, Journal of the Korean Physical Society, vol. 38, 268-272, March 2001 C. L. Lin and K. C. Fan, “Biometric Verification Using Thermal Images of Palmorsor Vein-patterns”, IEEE Trans. on circuits and systems for video technology, vol. 14, no. 2, 199-213, Feb. 2004 Shigeru Sasaki, Hiroaki Kawai, Satoshi Wakabayashi, “Product Exhibition of Palm Vein Authentication Technology”, FUJITSU, vol. 56, no. 4,346-357,2005 Naoto Miura, Goro Nagasaka, Takafumi Miyatake, “Finger vein pattern extraction based on repeated trials of line tracking and its application to personal authentication”, IEICE Transactions, vol. J86-D-II, no. 5,678-687,2003 C. L. Lin, T .; C. Chuang and K.K. C. Fan, “Palprint Verification Using Hierarchical Decomposition”, Pattern Recognition, vol. 38, 2639-2652, 2005 Hidefumi Obata, Morphology, Corona, 1996 M.M. Niemeier, B.M. V. Ginneken and J.M. Staal, “Automatic Detection of Red Relations in Digital Color Fundus Photographs”, IEEE Trans. on medical imaging, vol. 24, no. 5,584-592, May 2005

  However, even in the above-mentioned document, there is a problem that a special effort is required for an individual to be authenticated, for example, authentication is performed by pressing the back of the hand against the sensor port. Therefore, a new authentication method and a new authentication process required for it are required.

  In view of the above problems, an object of the present invention is to provide a personal authentication device that is simpler and more accurate for an individual to be authenticated and a personal authentication program used therefor.

  As a means for solving the above-described problems, a personal authentication device according to the present invention is based on a handle portion with a built-in light source, a light receiving portion that receives light emitted from the light source, and light received by the light receiving portion. And an information processing unit for performing personal authentication.

  In addition, although not necessarily limited in this means, it is preferable to have a visible light cut filter provided between the handle portion and the light receiving portion.

  Further, in this means, the information processing unit is not limited, but the information processing unit generates a back of the hand image data based on the light received by the light receiving unit, and a plurality of finger web data from the back of the hand image data. ROI from the finger web data creation unit to be created, the rotation / movement processing unit that performs at least one of rotation processing and movement processing on the back image data of the hand, and the back image data of at least one of the rotation processing or movement processing ROI region data extraction unit for extracting region data, vein pattern data extraction unit for extracting vein pattern data from the extracted ROI region data, and a personal vein pattern database in which individual vein pattern data to be authenticated is stored in advance Sections, vein pattern data extracted by the vein pattern data extraction section, and personal vein patterns It is also preferred to have a correlation calculation unit for calculating the correlation between the personal vein pattern data in the emissions database unit.

  Further, as another means for solving the above-described problem, a personal authentication program according to the present invention includes a back-of-hand image data creation unit for creating back-of-hand image data based on intensity data of light transmitted through a human hand on a computer. Performs at least one of a finger web data creation unit that creates a plurality of finger web data from image data, a rotation / movement processing unit that performs at least one of rotation processing and movement processing on the back of the hand image data, and rotation processing or movement processing. ROI region data extracting unit for extracting ROI region data from the back image data of the hand, vein pattern data extracting unit for extracting vein pattern data from the extracted ROI region data, and storing vein pattern data of an individual to be authenticated The personal vein pattern database section and vein pattern data extraction section A vein pattern data, the determination unit for calculating the correlation between the personal vein pattern data in the personal vein pattern database unit, characterized in that to function as a.

  As described above, according to the present invention, it is possible to provide a simpler and more accurate personal authentication device and a personal authentication program used therefor for an individual to be authenticated.

  Hereinafter, the personal identification program according to the present embodiment will be described. FIG. 1 is a diagram illustrating an outline of a personal authentication device according to the present embodiment. As shown in FIG. 1, the personal authentication device according to the present embodiment includes a handle unit 1 in which a light source 11 is incorporated, a light receiving unit 2 that receives light emitted from the light source 11 of the handle unit 1, and a handle unit 1. And a visible light cut filter 3 provided between the light receiving unit 2 and an information processing unit 4 that performs personal identification based on light received by the light receiving unit.

  As shown in FIG. 1, the handle portion 1 is a portion that is held by a person to be authenticated. The handle unit 1 has a built-in light source 11. When a person to be authenticated holds the handle unit, if the light is emitted from the light source 11, the light passes through the back of the hand and can be received by the light receiving unit 2. . In the present embodiment, by allowing a person to grip the handle, an appropriate tension can be generated on the back side of the hand, a clear blood vessel pattern can be generated on the back side of the hand, and the hand is in the vicinity of the light source 11. As a result, a clearer blood vessel pattern can be obtained. The shape of the handle portion 1 is not limited, and various forms can be adopted. For example, the shape of the handle portion 1 can be a form in which a light source is incorporated in a handle of a door. In this case, there is an advantage that the operation for opening the door and the personal authentication operation can be performed in a series of steps, and the person does not need a special operation, so that the personal authentication can be performed more easily. In addition, the example of the other form of the handle | steering-wheel part 1 is shown in FIG.

  The light source 11 incorporated in the handle portion 1 is not limited, and various light sources can be adopted. However, the wavelength of emitted light is preferably in the near infrared region, and more specifically. Specifically, it is preferably a light source including many wavelengths of 700 nm to 800 nm. This is because blood in veins containing a large amount of reduced hemoglobin absorbs near infrared light.

  The light receiving unit 2 receives light emitted from the light source 11 and outputs the light to the information processing unit 4. The configuration of the light receiving unit 2 is not limited, but for example, a CCD camera can be employed.

  A visible light cut filter 3 is provided between the handle portion 1 and the light receiving portion 2. By providing the visible light cut filter 3, it is possible to reduce the influence of a change in the proof condition and a scar on the back of the hand. The visible light region to be cut is not limited, but preferably has the ability to cut visible light of 750 nm or less. Further, the arrangement of the visible light cut filter 3 is preferably between the handle portion 1 and the light receiving portion 2, but in the vicinity of the light receiving portion 2, between the hand of the person to be authenticated and the light receiving portion 2 during personal authentication. It is more effective and preferable that it is arranged so as to be in between.

  The information processing unit 4 is a unit that performs personal recognition based on the light received by the light unit. FIG. 3 is a functional block diagram of the information processing unit 4 (hereinafter also referred to as “the information processing unit 4”) according to the present embodiment.

  As illustrated in FIG. 3, the information processing unit 4 includes a back-of-hand image data generation unit 41 that generates back-of-hand image data based on light received by the light-receiving unit, and finger web data that generates a plurality of finger web data from the back of the hand image data. The ROI region data is generated from the creation unit 42, the rotation / movement processing unit 43 that performs at least one of rotation processing and movement processing on the back image data of the hand, and the back image data of at least one of the rotation processing or movement processing. ROI region data extracting unit 44 for extracting, vein pattern data extracting unit 45 for extracting vein pattern data from the extracted ROI region data, and a personal vein pattern database in which individual vein pattern data to be authenticated is stored in advance Unit 46, vein pattern data extracted by vein pattern data extraction unit, and personal vein pattern And a determination unit 47 for calculating a correlation between the personal vein pattern data in the emissions database unit.

  The information processing unit 4 is not limited as long as it can perform personal recognition using the above processing. For example, a program for functioning as each of the above units is stored in a recording medium such as a hard disk of a computer. However, it may be realized by executing.

  The back of the hand image data creation unit 41 creates back of the hand image data based on the light intensity data received by the light receiving unit 2. FIG. 4 shows an example of the back of the hand when the back of the hand image data is represented as an image. As shown in FIG. 4, human hands and vein patterns appear in this figure.

  Next, the information processing unit 4 uses the finger web data creation unit 42 to create a plurality of finger web data from the back of the hand image data. Here, the “finger web” means the most depressed portion between the bones of each finger. By using this finger web data, the information processing unit 4 can correct the direction of the back of the hand, the position of the back of the hand, and the like, thereby improving the accuracy of authentication.

  It is more preferable to perform contrast adjustment on the back of the hand image data before starting the creation of finger web data. By doing in this way, the precision of finger web data creation can be raised more. An example of contrast adjustment is shown in FIG.

  Here, creation of finger web data will be described more specifically. First, the finger web data creation unit 42 creates hand outline data. Although the hand contour data is not limited, it is preferably a set of position data of a plurality of points constituting the hand contour, and an example of expressing the hand contour data as an image is shown in FIG. This is shown in FIG.

Then, the finger web data creation unit 42 includes two intermediate points (Wm, see FIG. 6) of an intersection between a certain point, for example, a portion extending from the wrist to the arm side in the contour of the hand, and the contour. Find the Euclidean distance from each point of the line and find its distribution. An example of this distribution graph is shown in FIG. And the minimum value of local curvature is calculated | required from this distribution, and several finger web position data are extracted. The finger web data is not limited, but includes a finger web (Fw1) between the index finger and the middle finger, a finger web (Fw2) between the middle finger and the ring finger, and a finger web (Fw3) between the ring finger and the little finger. It is preferable to obtain three finger web data from the viewpoint of improving authentication accuracy (see FIG. 6). Note that the Euclidean distance between the intermediate point Wm of the contour line and each point of the contour line is obtained by the following equation. In the following formula, D _E (i) is the Euclidean distance, X _Wm is the position data of the intermediate point at the x coordinate, and X _b (i) is the position data of the X coordinate at the point i of the contour line, Ywm Represents the Y coordinate position data at the intermediate point, and Yb (i) represents the Y coordinate position data at the contour point i.

  By doing in this way, the finger web data creation unit 42 according to the present embodiment can determine the position of the finger web and not only can perform various processes described later, but also raise the system of personal authentication. be able to.

Next, the rotation / movement processing unit 43 according to the present embodiment obtains a straight line passing through the finger webs Fw1 and Fw2 obtained above, obtains a rotation angle between the straight line and the X axis or the Y axis in the image data, The rotation process is performed so that the straight line is parallel to the X axis or the Y axis. Although not limited, for example, the angle between the straight line passing through the finger webs Fw1 and Fw2 and the X axis can be obtained by the following equation. In the following formula, α is the inclination angle of the straight line, Y _Fw3 is the Y coordinate position data on the finger web Fw3, Y _Fw1 is the Y coordinate position data on the finger web Fw1, and X _Fw3 is the X coordinate on the finger web Fw3. X _Fw1 represents the position data of the X coordinate in the finger web Fw1. For example, FIG. 8 shows the result of performing the rotation process on the image shown in the example of FIG.

  Next, the ROI area data extraction unit 44 extracts ROI area data from the back image data of the hand that has been subjected to at least one of the rotation process and the movement process. Here, the ROI region is a partial region of the back image of the hand and refers to a region of particular interest for personal authentication using a vein blood vessel pattern. The ROI region is not limited as long as it has the above-mentioned function. For example, the ROI region has a predetermined distance from the straight line passing through Fw1 and Fw3, and the parallel point is the same as the X coordinate of the finger web Fw2. A rectangular region having one side is preferable. Examples of this ROI area are shown in FIGS.

  Further, the vein pattern data extraction unit 45 extracts vein pattern data from the ROI region data. Specific processing will be described below.

The personal authentication device according to the present embodiment uses a transparent image of the back of the hand. In this case, the transmitted light becomes more difficult to transmit as the hand is thicker, but the thickness of the human hand is not uniform, resulting in uneven brightness and noise. Therefore, the vein pattern extraction unit 45 according to the present embodiment employs a technique based on morphology, although not limited thereto. Although the method based on the morphology is not limited, the min process and the max process are performed on a disk having a certain diameter around the target pixel, and the first min process is performed in both the vertical and horizontal directions smaller than the diameter. The line segment disappears. As a result, a background image showing the distribution of luminance villages is obtained by hiding the vein portion. Then, this background image is subtracted from the image of the ROI area shown in FIG. Note that FIG. 10 shows the obtained background image, and FIG. 11 shows an image obtained by removing luminance unevenness from the image shown in FIG. In addition, equations for min processing, maxsy processing, and opening processing are shown below.

Here, X _B represents opening by the structural element B of the set X. B ^S represents a target set of structural elements B.

  In addition, the vein pattern data extraction unit 45 according to the present embodiment performs an opening process on a plurality of directions using a straight line having a predetermined width as a linear structural element (see FIG. 12 for an example of a plurality of directions). The predetermined width of the straight line is determined by the width of the blood vessel. The example of FIG. 12 is an example of 0 °, 30 °, 60 °, 90 °, 120 °, and 150 °, and examples of images obtained by performing an opening process with linear structural elements along each of FIG. 13 to FIG. This is shown in FIG. Since this opening process is to perform predetermined min processing and max processing centering on the target pixel, the line length less than the predetermined pixel is lost in each direction in the first min processing, while the next max The line segment of a predetermined length is returned to the original state by processing. In addition, since the image obtained as a result of the opening process with respect to each direction has each image directionality, image enhancement is performed using linear structural elements in different directions. Therefore, the vein pattern data extraction unit 45 according to the present embodiment gives the maximum gray value in the image obtained as a result of the opening process for the plurality of directions to each point of the enhanced image, and creates a new enhanced image. An example of this image is shown in FIG.

  Next, the vein pattern data extraction unit 45 creates a binary image from the luminance image obtained here. As a process for creating this binary image, a binarization process can be cited, and the image is separated into an object area (value of 1) and a background area (value of 0). Although this binarization processing is not limited, it is preferable to use a threshold value as a threshold value when the histogram in an image is divided into two and divide it into a reference. A binary image obtained as a result is shown in FIG.

  The vein pattern data extraction unit 45 further converts the obtained binary image into a line image having a width of 1 pixel. The result is shown in FIG.

  Note that the extracted vein pattern data alone cannot authenticate an individual, and a personal vein pattern database unit 46 that stores in advance the vein pattern data of an individual to be authenticated is necessary. The personal vein pattern database unit 46 is not limited, but data for identifying an individual (for example, name data and ID data), and vein pattern data corresponding to the data for identifying the individual, It is preferable that one or two or more are stored. FIG. 22 shows an example of a thin line image of the stored vein pattern.

  The determination unit 47 determines whether or not they are the same person by calculating the correlation between the vein pattern data extracted by the vein pattern data extraction unit and the personal vein pattern data in the personal vein pattern database unit. The determination method is not limited as long as it can be realized, but a method using matching of an end point or a branch point (maneuver) of a fingerprint ridge is preferable. The matching is not limited, but it is preferable to check not only the appearance position and angle coincidence of the minutia but also the appearance position and angle coincidence (fine matching) of all points between the minutiae. . FIG. 23 shows an example of the minutiae extracted from FIG. It is very useful to register not only the fine line image of the vein pattern but also this minutiae in the vein pattern database unit 46. An example of registered minutiae is shown in FIG.

The determination unit 47 first extracts minutiae in minutia matching. The minutiae is extracted by the following formula. In the following formula, R (k) represents a gray value near 8 of a certain point A. When Cn = 6, A is a branch point, and when Cn = 2, A means an end point.

  Next, the determination unit 47 removes false feature points caused by noise generated in the above-described processing, and performs matching on the remaining feature points.

The determination unit 47 also assigns a direction code to each minutiae. For the direction code, the lower right pixel (i _{0 + 1} , j _{0 + 1} ) is 1, the right pixel (i _{0 + 1} , j ₀ ) is 2, ..., the lower pixel (i ₀ , j _{0 + 1} ) is 8 and left. Numbers are assigned in order around the X-coordinate, Y-coordinate, end point, branch point type, and direction code. That is, the registered minutiae P stored in the personal vein pattern database unit 46 and the input minutiae Q obtained here are expressed by the following equations.

  Here, Xi and Xj are X coordinates, Yi and Yj are Y coordinates, SDi and SDj are direction codes, and Ki and Kj are types of end points and branch points.

Although it is not necessarily limited, the determination part 47 matches a minutiae in steps. First, it is determined whether or not the following conditions are satisfied between the registered minutiae and the input minutiar, and more detailed matching is performed for those that match.
(1) The distance between minutiae is less than or equal to threshold Th _dt (2) The direction difference between minutiae is less than or equal to threshold Th _θt (3) Type of minutia matches (4) Distance between minutiae Minimal sum (5) 1 to 1 correspondence

In the detailed matching, first, the positional deviation is finely adjusted based on the position and direction of each branch point (an example of an image after adjusting the positional deviation is shown in FIG. 25). Then, tracing is performed for each vein connection region from each branch point, and the X, Y coordinates and direction code are extracted to represent the point. The total sum θ _sum of direction differences between the points and the total sum D _sum of the distances between the points are authenticated according to the following equations.

  Here, num = M + N, M, N indicate the number of branch points and end points. It also indicates the number of points from the count leaf start point to the next branch point or end point. angle1 indicates a direction code at each point of the registered image, and angle2 indicates a direction code at each point of the input image. X1 and X2 indicate the X coordinate of each point in the registered image, and Y1 and Y2 indicate the Y coordinate of each point in the registered image.

Moreover, the collation rate is shown as follows.

That is, the determination of whether or not they are the same person is expressed by the following expression.

  Increasing Thd2 and Thθ2 makes it easier for the person to be authenticated, and at the same time increases the rate at which others are mistakenly authenticated. Therefore, the threshold values Thd2 and Thθ2 need to set an appropriate operating point at the time of operation in consideration of the balance between the person rejection rate and the other person authentication rate.

  Therefore, as described above, personal authentication can be performed more simply and reliably by the personal authentication device according to the present embodiment. In particular, with this personal authentication device, it is possible to perform personal authentication simply by grasping the handle to open the door, etc., no special operation is required, no key form such as a card is required, theft or forgery Convenience, such as being able to prevent, becomes high. Furthermore, a system that is robust against rotation and misalignment of the hand can be configured, and even a method of grasping the handle has higher accuracy.

  Here, the above personal recognition device was actually created and the actual recognition process was performed. The experiment was conducted with 30 registrants holding the door handle naturally, taking each person's image twice, and learning 10 vein patterns from 10 people in each hand, totaling 600 vein patterns. In addition, five non-registered people are added to 30 registrants, and 800 vein patterns (600 registrants and 200 unregistered people) are obtained in the same manner, and this is a registered or unregistered person. I confirmed the pros and cons of such certification. The results are shown in Table 1.

According to the results in Table 1, the recognition rate is 98% or more for registrants (out of 600, 4 are false recognitions, 4 are rejected), and 99% or more for unregistered persons. It was possible to obtain a rejection rate (two of the 200 sheets that were misrecognized), confirming the usefulness of the present invention. FIG. 26 shows an example of a fine line image of a vein pattern acquired in this embodiment.

It is a schematic diagram of a personal authentication device concerning an embodiment. It is a figure which shows the other example of a handle part. It is a functional block diagram of an information processing part. It is a figure which shows the example of the back image of a hand. It is a figure which shows the example of the back image of the hand which performed contrast adjustment. It is a figure which shows the outline of the back of a hand. It is a figure which shows distribution of Euclidean distance. It is a figure of the example which performed the rotation process and extracted the ROI area | region. It is a figure which shows the example of a ROI area | region. It is a figure which shows the example of the background image in a ROI area | region. It is a figure which shows the example of the image which performed illumination correction using FIGS. 9-10. It is a figure which shows the example of a structural element. It is a figure which shows the example of the result of having performed the opening process in the 0 degree direction. It is a figure which shows the example of the result of having performed the opening process in the direction of 30 degree | times. It is a figure which shows the example of the result of having performed the opening process in the direction of 60 degree | times. It is a figure which shows the example of the result of having performed the opening process in the direction of 90 degree | times. It is a figure which shows the example of the result of having performed the opening process in the direction of 120 degree | times. It is a figure which shows the example of the result of having performed the opening process in the direction of 150 degree | times. It is a figure which shows the example of an emphasized image. It is a figure which shows the example of a binary image. It is a figure which shows the example of a thin line image. It is a figure which shows the example of the thin line image stored in the vein pattern database part. It is a figure which shows the example of a minutia. It is a figure which shows the example of the minutiae stored in a vein pattern database part. It is a figure which shows the example of the minutia which correct | amended position shift. It is a figure which shows the example of the fine line image of the vein pattern acquired in the Example.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Handle part, 2 ... Light-receiving part, 3 ... Visible light cut filter, 4 ... Information processing part, 11 ... Light source

Claims (4)

A handle portion with a built-in light source;
A light receiving unit for receiving light emitted from the light source;
An information processing unit that performs personal authentication based on light received by the light receiving unit.   The personal authentication device according to claim 1, further comprising a visible light cut filter provided between the handle portion and the light receiving portion. The information processing unit
A back image data creating unit for creating back image data of the hand based on the light received by the light receiving unit;
A finger web data creation unit for creating a plurality of finger web data from the back image data of the hand;
A rotation / movement processing unit that performs at least one of rotation processing and movement processing on the back of the hand image data;
An ROI region data extraction unit that extracts ROI region data from back image data of a hand that has been subjected to at least one of rotation processing and movement processing;
A vein pattern data extraction unit for extracting vein pattern data from the extracted ROI region data;
A personal vein pattern database unit that prestores personal vein pattern data to be authenticated;
A correlation calculation unit for calculating a correlation between the vein pattern data extracted by the vein pattern data extraction unit and the personal vein pattern data in the personal vein pattern database unit;
The personal authentication device according to claim 1. On the computer,
The back image data creation unit for creating the back image data of the hand based on the intensity data of the light transmitted through the human hand,
A finger web data creation unit for creating a plurality of finger web data from the back image data of the hand;
A rotation / movement processing unit that performs at least one of rotation processing and movement processing on the back of the hand image data,
ROI region data extraction unit for extracting ROI region data from back image data of a hand that has been subjected to at least one of rotation processing and movement processing;
A vein pattern data extraction unit for extracting vein pattern data from the extracted ROI region data;
An individual vein pattern database unit that stores in advance the vein pattern data of individuals to be authenticated;
A personal authentication program for functioning as a determination unit for calculating a correlation between the vein pattern data extracted by the vein pattern data extraction unit and the personal vein pattern data in the personal vein pattern database unit.