KR20060134547A - Apparatus and method of fingerprint recognition - Google Patents

Abstract

A device and a method for recognizing a fingerprint are provided to perform precise fingerprint recognition based on composition of a partial fingerprint image irrespective of skewed sliding when a fingerprint is slid. A fingerprint sensor(10) obtains the fingerprint image. A sliding information extractor(30) detects a relative sliding speed/direction among the obtained partial fingerprint images. An ROI(Region Of Interest) extractor(80) extracts a ridge inclusion level of each partial fingerprint image. A storing part(40) stores the partial fingerprint image, sliding information, and ridge information. A movement calculator(50) calculates an optimal moving point of each partial fingerprint image in a coordinate system to compose the partial fingerprint image by using the ridge information. A composer(60) composes each partial fingerprint image based on one coordinate system by applying the moving point to the sliding speed/direction. A fingerprint recognizer(70) advances the recognition based on the composed fingerprint image.

Description

Fingerprint recognition device and method {APPARATUS AND METHOD OF FINGERPRINT RECOGNITION}

1 is a view showing an example of a slide type fingerprint sensor exterior structure;

Fig. 2 shows an example of a local fingerprint image obtained by a slide type fingerprint sensor.

3 is a view showing an example of a fingerprint image when sliding in the long axis direction

4 is a view showing an example of a fingerprint image when sliding in the long axis direction skew

5 is a diagram illustrating an example of moving a matched fingerprint image in skew sliding;

Figure 6 is a block diagram of a fingerprint recognition device according to the present invention

7 illustrates an example of a local fingerprint image according to the present invention.

8 is a flowchart of a fingerprint recognition method according to the present invention.

<Explanation of symbols for the main parts of the drawings>

10: fingerprint sensor 20: fingerprint image processing unit

30: sliding information extraction unit 40: memory unit

50: moving calculation unit 60: matching unit

70: fingerprint recognition unit 80: ROI extraction unit

The present invention relates to a fingerprint recognition system.

In the security and security system technology, a method of using biometric information is used as a means for authenticating legitimacy of a person entering a building or a user of a specific device. Iris information or fingerprint information is used as biometric information for authentication, and various biometric authentication methods are used, ranging from authentication methods based on iris recognition to authentication methods based on fingerprint recognition. The biometric information-based authentication system is a method for not only authentication of the user of the building but also information protection or personal identification, and is used instead of the existing password method or ID card method.

In a system for authentication based on fingerprint recognition, a means for acquiring fingerprint information, a means for extracting a feature from the acquired fingerprint information, and a feature for analyzing the extracted feature and comparing the registered fingerprint information with the pre-registered fingerprint information are authenticated. Means;

Such a fingerprint recognition system is applied to a mobile terminal such as a PDA or a mobile phone because it has advantages such as mechanical simplicity of a sensor for authentication and high recognition accuracy of an authentication algorithm.

A fingerprint recognition sensor is used as a means for obtaining fingerprint information. Fingerprint sensors are classified into optical, thermal and semiconductor types, and mobile terminals are mainly equipped with semiconductor sensors due to space constraints. Semiconductor sensors can be classified into area type and slide type. However, since the space fingerprint recognition sensor has a large space occupied by the mobile terminal on which the sensor is mounted, the slide fingerprint recognition sensor having a relatively small occupied space is mainly mounted on the mobile terminal to exhibit an effect.

The slide-type fingerprint sensor reads local fingerprint images by sliding a finger and then performs a fingerprint recognition based on obtaining an intact fingerprint image by composing the local fingerprint images into one image. do.

Conventional partial fingerprint image matching methods sequentially superimpose the partial fingerprint image input from the fingerprint sensor onto the matched fingerprint image and update the matched fingerprint image by matching relative brightness values of the overlapped regions. We are taking a sequential composition.

However, in the sliding fingerprint recognition technique, partial fingerprint images are obtained and matched to form a single fingerprint image. Therefore, the recognition performance and the result are different depending on the type of the user's finger sliding on the fingerprint sensor for fingerprint recognition. It depends greatly. In particular, when skewed sliding occurs during sliding, it is very difficult to match partial fingerprint images into one image.

In addition, the fingerprint recognition system applied to a mobile terminal generally limits the size of the input image to a predetermined predetermined size for fingerprint recognition due to limited computing resources, and is optimized for the limited image size. When the skew sliding occurs, it is impossible to predict the skewed degree, which makes it impossible to predict the used memory space, thereby reducing the efficiency of using memory resources.

SUMMARY OF THE INVENTION An object of the present invention is a fingerprint recognition apparatus capable of performing accurate fingerprint recognition in spite of sliding sliding, in a system for recognizing a fingerprint based on the composition of a partial fingerprint image; To provide that method.

According to another aspect of the present invention, in a system for recognizing a fingerprint based on the registration of partial fingerprint images, the sliding speed between partial fingerprint images and the sliding speed when a skew occurs depending on the sliding habit of the user in the sequential matching method The present invention provides a fingerprint recognition device and a method for performing accurate fingerprint recognition by moving a partial fingerprint image to an optimal coordinate system based on the detected information to achieve partial fingerprint image registration.

It is still another object of the present invention to obtain a relative sliding speed and direction between adjacent neighboring partial fingerprint images when sliding for fingerprint recognition in a system for recognizing a fingerprint based on the composition of partial fingerprint images. By calculating the optimal coordinate system for registration of partial fingerprint images based on this, the partial fingerprint images are matched to solve the problem of calculation time and memory inefficiency required for matching and recognition, and maximize the amount of fingerprint ridge information. The present invention provides a fingerprint recognition device and a method for improving a fingerprint recognition success rate for a skew sliding.

The fingerprint recognition apparatus of the present invention includes a fingerprint image acquisition means, means for calculating a relative sliding speed and direction between partial fingerprint images inputted from the fingerprint image acquisition means, and fingerprint ridge information of the partial fingerprint image inputted from the fingerprint image acquisition means. Means for extracting the partial fingerprint images, their sliding information and fingerprint ridge information, and means for calculating the degree of movement of each partial fingerprint image using the stored partial fingerprint image and its sliding information and fingerprint ridge information. And means for matching partial fingerprint images stored in the storage means to one fingerprint image using the calculated movement degree, and means for performing fingerprint recognition based on the matched fingerprint image.

The fingerprint recognition method of the present invention comprises the steps of: obtaining a partial fingerprint image, obtaining relative sliding speeds and directions and fingerprint ridge information between the obtained partial fingerprint images, and using the speed and direction and fingerprint ridge information; Calculating a degree of movement for image registration, and matching partial fingerprint images by reflecting the calculated movement information.

EXAMPLE

Figure 1 shows an example of the slide structure of the fingerprint sensor appearance. Here, the structure in which the fingerprint sensor 102 of the slide type is mounted on the mobile terminal 101 is shown. The fingerprint sensor 102 acquires a partial and continuous partial fingerprint image by sliding a user's finger.

2 shows an example of a local fingerprint image obtained by a slide type fingerprint sensor. When the user slides the thumb 103 against the fingerprint sensor 102 at a predetermined speed, partial and continuous fingerprint images 104 to 107 are obtained.

As shown in FIG. 2, the fingerprint image of the user is obtained by being sliced into partial, adjacent, and continuous forms. The partial fingerprint images read from the fingerprint sensor 102 are matched with one fingerprint image, and the intact fingerprint image matched with one fingerprint image is compared with a pre-registered fingerprint image (may be a database), thereby validating the user. It will be used as a means of demonstrating this.

The present invention will provide a means for accurately matching and recognizing sliding partial fingerprint images based on the sequential matching method regardless of skew during sliding.

3 and 4 show examples of registration fingerprint images according to the sliding angle of the user. FIG. 3 shows an example of a sliding fingerprint image in the long axis direction of the fingerprint sensor, and FIG. 4 shows an example of a fingerprint image in sliding skew.

In the sequential matching method using the slide sensor, as shown in Figs. 3 and 4, if there is sliding in the short axis direction in addition to the sliding in the long axis direction, there is a restriction on the optimization expression of the fingerprint information obtained from the fingerprint sensor. In the sequential matching method, since the next sliding direction is not known in advance, when the skew sliding occurs, as shown in FIG. 4, the finally matched fingerprint image may exceed a given total fingerprint image size. In this case, the fingerprint ridge information for the portion beyond the entire fingerprint image size cannot be represented in the final fingerprint image.

Therefore, in order to maximize the information amount of the skewed sliding image as shown in FIG. 4 in the sequential matching method, the information amount of the fingerprint ridges of the ROI (Region Of Interest) pixels of the matched fingerprint image and the position information of the ROI itself are determined. Must be used to move the matched fingerprint image. The present invention provides a method and apparatus for increasing the success rate of fingerprint recognition by maximizing the amount of fingerprint ridge information through the calculation of the optimal degree of movement and the optimal movement using the same.

In addition, when a skew sliding occurs in the sequential matching method, an optimal moving point of the matched image will be determined by looking at the finally matched image. By doing so, it will be possible to predict and confirm the skewed degree, and increase the efficiency of memory usage by ensuring the predictability of the memory space to be used for sequential matching. In addition to the calculation time for the sequential matching, the additional time required for the calculation time for moving the finally matched image to the new memory space will be minimized.

In particular, it is possible to improve fingerprint recognition performance by reducing computation time and memory usage in a mobile terminal having limited computing resources, and solve the problem of fingerprint image registration in skew sliding using a slide sensor.

To this end, in the present invention, the relative sliding speed and direction between the adjacent partial fingerprint images are first calculated. The ROI pixels for obtaining the fingerprint ridge information amount are extracted from each partial fingerprint image, and the degree of inclusion of the fingerprint ridge is extracted and examined. The optimal coordinate system moving point is calculated using the sliding speed and direction between the partial fingerprint images and the fingerprint ridge information.

In the last step, by applying the calculated moving point to the sliding speed and direction to match each of the partial fingerprint images with respect to the image coordinate system to generate one complete fingerprint image and to use it to perform fingerprint recognition, Compared with the conventional sequential matching method, the optimal matching image is generated for the sliding sliding with less computation time and memory usage.

Figure 5 shows an example of moving the matched fingerprint image in the skew sliding. Severe skew sliding occurred in the fingerprint image before the movement, indicating that the amount of ridge information available in the fingerprint image was damaged. However, by moving the partial fingerprint images on the basis of the image coordinate system based on the sliding speed and the direction search information according to the present invention, ROI in the partial fingerprint image, that is, the amount of fingerprint ridge information, as shown in the fingerprint image after the movement. Likewise, the amount of fingerprint ridge information is maximized in an amount sufficient for fingerprint recognition.

6 shows a configuration of a fingerprint recognition device according to the present invention. The fingerprint recognition device shown in Fig. 6 can be mounted in the mobile terminal. The fingerprint recognition apparatus according to the present invention includes a fingerprint sensor 10 for acquiring a fingerprint image, a fingerprint image processor 20 for processing partial fingerprint images of a user read by the fingerprint sensor 10, and the fingerprint image processor ( 20, a sliding information extractor 30 for extracting relative sliding information between partial fingerprint images, and an ROI extractor 80 for extracting the amount of fingerprint ridge information from the partial fingerprint image, and the partial fingerprint images, respectively. Memory unit 40 for storing sliding information and ROI information, a movement calculation for calculating an optimal degree of movement for matching fingerprint images using partial fingerprint images, sliding information, and ROI information stored in the memory unit 40. The unit 50 uses a matching unit 60 to configure partial fingerprint images into a single fingerprint image based on the result of the optimal movement calculation, and uses the matched fingerprint image. It comprises a fingerprint recognition unit 70 for performing the recognition of the fingerprint image.

The fingerprint sensor 10 is a slide type semiconductor fingerprint sensor. The slide type semiconductor fingerprint sensor scans a fingerprint and reads the fingerprint in the form of a partial fingerprint image when the user slides the finger on the recognition window of the sensor at a predetermined speed.

The partial fingerprint image read from the fingerprint sensor 10 is input to the fingerprint image processor 20. The fingerprint image processing unit 20 performs sampling driving of the fingerprint sensor 10, and converts the partial fingerprint images read into digital signals to provide a basis for performing pixel-based fingerprint recognition. In addition, as will be described later, the fingerprint image processing unit 20 applies the same gain to all areas of the image so that the average brightness is the same before the search for the sliding speed and the direction of the reference image and the target image. It also performs the process of adjusting.

The sliding information extractor 30 extracts the speed and the direction as sliding information of the partial fingerprint images. That is, relative speed information and direction information between two adjacent partial fingerprint images are extracted.

The ROI extractor 80 calculates ROI pixels in which a fingerprint ridge exists in the input partial fingerprint image. To this end, the partial fingerprint image is divided into blocks of a predetermined size, and the distribution of fingerprint ridges in each block is determined to determine whether to register an ROI.

The memory unit 40 stores partial fingerprint images sequentially input, sliding information about each partial fingerprint image, and the ROI information.

When the sliding operation of the user is completed, the movement calculating unit 50 uses the relative sliding information between the partial fingerprint images stored in the memory unit 40 and the ROI information when the entire partial fingerprint image is matched without an actual image matching process. The ROI information and the fingerprint ridge information amount of the fingerprint image are calculated, and the optimal movement information is obtained.

The matching unit 60 matches each partial fingerprint image into a single fingerprint image based on the optimal movement information, and the fingerprint recognition unit 70 recognizes and authenticates the corresponding user fingerprint using the matched final fingerprint image. Will be performed.

7 shows an example of a local fingerprint image according to the present invention. In FIG. 7, two partial fingerprint images are represented, which are adjacent and consecutive partial fingerprint images. The first partial fingerprint image 110 is a current partial fingerprint image input from the fingerprint sensor 10, and the second partial fingerprint image 120 is a previous partial fingerprint image input from the fingerprint sensor 10. Here, the current partial fingerprint image and the previous partial fingerprint image mean one of the following two cases.

First, when real-time skew correction and registration are performed, the partial fingerprint image currently input is the current partial fingerprint image, and the partial fingerprint image already input at the previous time point corresponds to the previous partial fingerprint image.

Second, when the skew correction and registration are performed collectively after the completion of the input of all partial fingerprint images, if the partial fingerprint image selected from among the partial fingerprint images is the current partial fingerprint image, the selected partial fingerprint image is selected. This is the case where the partial fingerprint image input at the point in time immediately before the input is the previous partial fingerprint image.

In either case, the matching and recognition method based on the skew correction of the partial fingerprint image, which will be described later, will be equally applied.

When the first partial fingerprint image 110 is used as a reference image, the second partial fingerprint image 120 becomes a target image. In contrast, when the second partial fingerprint image 120 is used as the reference image, the first partial fingerprint image 110 becomes a target image. In the present invention, in order to extract and correct relative sliding information between partial fingerprint images, a portion of the target image 120 is a target-search slice 121 and a portion of the region of the reference image 110 is a reference slice 111. Set each to. The detailed method using the target image-search slice, the reference image-reference slice will be described later.

8 is a flowchart of a fingerprint recognition method according to the present invention.

A first step S10 is a step of acquiring a partial fingerprint image, and a second step S20 is a step of determining whether an input partial fingerprint image is an initial input. The third step S30 is a step of extracting sliding information relative to the previously inputted partial fingerprint image when the inputted partial fingerprint image is the second and subsequent partial fingerprint images. The fourth step (S40) is a step of extracting the ROI for obtaining the amount of fingerprint ridge information from the partial fingerprint image, the fifth step (S50) is a memory unit 40 to extract the extracted partial fingerprint image, sliding information and the corresponding ROI information Save to. The sixth step S60 is to continuously determine whether there is a fingerprint sensor input. If there is no more fingerprint sensor input in this step, the process moves to the seventh step S70 to determine an optimal moving point between the partial fingerprint images. Perform the calculation. The eighth step S80 is a fingerprint image registration and recognition step in which each partial fingerprint image is composed of one intact fingerprint image by reflecting the skew corrected information based on the optimum moving point.

The fingerprint recognition method represented in FIG. 8 will be described in more detail with reference to the accompanying drawings.

As the sliding operation of the user starts and the first partial fingerprint image input is detected from the fingerprint sensor 10, the fingerprint recognition system according to the present invention operates.

The partial fingerprint image is acquired by sensing an input from the fingerprint sensor 10 and storing the partial fingerprint image input from the fingerprint sensor 10 in a predetermined region of the predetermined memory unit 40 when sliding is detected in the sensor.

Since the sliding information cannot be extracted when the first partial fingerprint image is input, it waits for the next partial fingerprint image input.

If there is more than one input partial fingerprint image, sliding information extraction is performed.

In other words, the partial fingerprint image T (N) currently input and the partial fingerprint image T (N-1) input in the previous step stored in the memory are read to extract relative sliding directions and speed information between the two partial fingerprint images. The sliding direction and the speed are extracted by comparing brightness values of overlapping images between two adjacent partial fingerprint images.

To this end, one image is used as a reference image and the other image is used as a target image, and a point where the difference in brightness values of overlapping pixels between the reference image and the target image is minimized is found. Here, the reference image and the target image are continuous partial fingerprint images input from the fingerprint sensor 10 and have the same image size. In order to efficiently perform the minimum point search of the brightness values between the adjacent partial fingerprint images, some specific regions of the target image are set as the search slices, and some specific regions of the reference image are set as the reference slices.

For example, in FIG. 7, the specific image area of the first partial fingerprint image 110 is set as the reference slice 111, the specific image area of the second partial fingerprint image 120 is set as the search slice 121, and While moving the two-part fingerprint image 120 in the long axis (X) and short axis (Y) directions of the fingerprint sensor 10, the brightness value of each pixel overlapping with the reference slice 111 is obtained, and the difference is minimized. Search for a point.

Taking a partial fingerprint image on the memory unit 40 shown in FIG. 6 as an example, T (N-1) and T (N) are read, and T (N) is in the long axis (X) and short axis (Y) directions. Moving toward, it searches for a point where the difference in brightness value of each pixel overlapping the reference slice of T (N-1) becomes the minimum. That is, when the target image is superimposed on the reference image, the point at which the difference in brightness between the pixels of the target image superimposed on the reference slice image and each pixel of the base slice image is minimized is searched for.

Next, when the difference between the brightness values of the overlapped areas becomes minimum, the speed and direction of sliding are calculated by calculating the relative degree of pixel movement between the reference slice coordinate system and the target slice coordinate system. That is, the two partial fingerprint images are calculated by calculating the relative degree of movement in the long axis (X) and short axis (Y) directions of the target image when the difference between the brightness values of the overlap regions is minimum based on the reference slice image. The relative speed and direction of the liver can be obtained.

As such, two adjacent partial fingerprint images may have a common overlapping area, or may not have an overlapping area when the sliding speed of the user is faster than the sampling rate of the fingerprint sensor.

In addition, the position and size of the reference slice image 111 may be variable or fixed. The position and size of the reference slice image 111 are fixed while the sliding direction and the speed are obtained, and the sliding of the partial fingerprint image obtained in the previous step is performed. When the new partial fingerprint image is input from the fingerprint sensor 10 according to the speed and the direction information, its position and size are variably adjusted. This is to more efficiently search for new partial fingerprint images and extract sliding information efficiently. In addition, prior to the search for the sliding speed and the direction, by adjusting the brightness value by applying the same gain over the entire area of the image such that the average brightness value of the reference image and the target image are the same, the image is adjusted. It increases the efficiency and accuracy of the search.

Next, the ROI extractor 80 divides the input partial fingerprint image into blocks having a predetermined size, and determines the ROI registration based on the distribution of the fingerprint ridges in each block. That is, the ROI pixels in which the fingerprint ridges exist in the partial fingerprint image are calculated.

Next, the ROI registration information along with the calculated sliding speed, direction information, and brightness difference information at that time is synchronized with the input partial fingerprint image and stored in the memory unit 40.

Repeat the above process until the last partial fingerprint image is inputted, and all partial fingerprint images T (1), T (2), ..., T (N-1), T (N) and their The speed and direction, which are relative sliding information between the partial fingerprint images and the adjacent fingerprint images, are extracted, and the ROI registration information for calculating the amount of fingerprint ridge information is stored in the memory unit 40.

When the sliding operation of the user is finished, the movement calculating unit 50 uses the sliding information (speed and direction) of each partial fingerprint image stored in the memory unit 40 when the entire partial fingerprint image is matched without an actual image matching process. Calculate ROI information and fingerprint ridge information amount of fingerprint image. That is, before performing the actual image registration process, the ROI position information and the fingerprint ridge information amount of the image to be virtually matched are calculated. Here, the fingerprint ridge information amount of the entire fingerprint image to be matched predicts the fingerprint ridge information amount of the ROI pixels included in each partial fingerprint image by using the relative velocity and direction information of each partial fingerprint image, and predicts the prediction of all partial fingerprint images. Accumulating by applying to, it is possible to calculate the amount of fingerprint ridge information of the entire fingerprint image without the actual matching process.

And based on the ROI location information of the virtual image to be matched and the amount of fingerprint ridge information obtained, the point of the maximum amount of information of the overlapped region while moving a given matching image size over the entire fingerprint image to be matched. Find it. The optimum degree of movement (optimal movement point) as shown in Fig. 5 is obtained by calculating the relative degree of movement between the point where the information amount of the overlapped area is maximum and the reference position of a given registration image. That is, based on the predicted fingerprint ridge information amount and the position information of the ROI pixels, while moving the given matched image size over the entire fingerprint image to be matched, the point where the information amount of the overlapped area is maximized is found, The degree of movement of the entire fingerprint image to be matched is calculated by calculating the degree of relative movement with respect to the reference position. Here, the relative movement degree includes both the long axis and the short direction of the fingerprint sensor.

In the present invention, two adjacent partial fingerprint images are not matched immediately after the relative sliding direction and speed are calculated, and the movement of the entire fingerprint image to be matched can be maximized at a given image size, so that the amount of fingerprint ridge information of the entire fingerprint image to be matched can be maximized at a given image size. After the degree is calculated, it is matched collectively using the optimal fingerprint movement information, the sliding direction and the speed. Here, the sliding direction and speed information between all consecutive adjacent partial fingerprint images starts from the partial fingerprint image input from the fingerprint sensor 10 at the start of sliding of the user, and the fingerprint sensor 10 at the end of sliding of the user. Relative sliding directions and velocities obtained from combinations of partial fingerprint images sequentially generated from the partial fingerprint images to the input partial fingerprint images.

When the correction for the skew sliding is completed as described above, the fingerprint image matching unit 60 matches the partial fingerprint images stored in the memory unit 40 to one fingerprint image by using the sliding speed and the direction information. In this case, by using the sliding speed and the direction information of the adjacent partial fingerprint image, matching is limited to the fingerprint image region except for the region overlapping with the partial fingerprint image to be subsequently matched, thereby reducing unnecessary calculation time and forming the entire matched image. Can be.

When matching is completed, the matched image, sliding information, and ROI information of the matched image are transmitted to the fingerprint recognition unit 70, and the fingerprint recognition unit 70 extracts feature information of one intact fingerprint image. The authenticity of the user is verified and authenticated based on the characteristic information.

According to the present invention, in the fingerprint recognition using the slide-type fingerprint sensor, the user's sliding information is generated as one completed fingerprint image using only the input partial fingerprint image information, and at this time, the fingerprint that may occur in the user's skew sliding By effectively solving the loss of ridge information, the success rate of fingerprint recognition can be improved.

In addition, by providing the direction information on the sliding sliding to the fingerprint recognition algorithm (fingerprint recognition unit), it is possible to secure stable fingerprint recognition performance even during the sliding sliding without increasing the fingerprint recognition time, and can cope with various sliding habits of the user. have.

The present invention can recognize partial fingerprint images input from a slide type fingerprint sensor while minimizing matching errors in a mobile terminal environment with limited computing resources, and according to a sliding habit of a user when a sliding fingerprint sensor is mounted Enables accurate fingerprint matching and recognition despite sliding.

Claims (22)

Means for acquiring a fingerprint image, means for detecting a relative sliding speed and direction between the acquired partial fingerprint images, means for extracting a degree of fingerprint ridge inclusion of each acquired partial fingerprint image, the partial fingerprint image, sliding information, and ridge information Means for calculating an optimal coordinate system movement point of the partial fingerprint images for partial fingerprint image registration using the fingerprint ridge information, and applying the movement point to sliding speed and direction to apply each partial fingerprint image to one And means for performing matching based on the coordinate system and means for performing recognition based on the matched fingerprint image. The method of claim 1, wherein the sliding speed and the direction information are obtained by comparing one of two consecutive partial fingerprint images as a reference image and the other as a target image by comparing the reference image and the target image. Fingerprint recognition device. 2. The fingerprint ridge information amount of claim 1, wherein the fingerprint ridge information amount of the ROI pixels included in each partial fingerprint image is predicted using relative speed and direction information of each partial fingerprint image, and the prediction is performed for all partial fingerprint images. Fingerprint recognition device, characterized in that to accumulate the results to obtain the amount of fingerprint ridge information of the entire fingerprint image. The method of claim 1, wherein the optimal coordinate system movement point is based on the amount of fingerprint ridge information and the ROI location information in the partial fingerprint image, and superimposes a given matched image size on the entire fingerprint image to be matched to maximize the information amount of the overlapped region. And obtaining the point by calculating relative movement information with respect to the reference position of the given registration image. 2. The fingerprint recognition apparatus according to claim 1, wherein the fingerprint image acquisition means, sliding information detection means, fingerprint ridge information extraction means, storage means, coordinate system calculation means, and matching means are mounted in a mobile terminal. As a reference image, one of a fingerprint sensor for sequentially and partially acquiring a fingerprint image according to the sliding of a user, storage means for storing partial fingerprint images detected by the fingerprint sensor, and one of the consecutive adjacent partial fingerprint images, And a means for detecting a relative sliding direction and a speed between adjacent partial fingerprint images based on the comparison of the brightness values of the other one as the target image. Obtaining a partial fingerprint image, obtaining a relative sliding speed and direction and fingerprint ridge information between the obtained partial fingerprint images, and using the speed and direction and fingerprint ridge information, a degree of movement for partial fingerprint image registration. And calculating partial fingerprint images by reflecting the calculated movement information. 8. The fingerprint recognition method according to claim 7, wherein the relative sliding information between the partial fingerprint images is obtained by comparing two adjacent partial fingerprint images. The fingerprint recognition method according to claim 7, wherein the sliding information is obtained for both the long axis direction and the short direction of the fingerprint sensor. The method of claim 7, wherein the relative sliding information between the partial fingerprint images is a comparison between the target image and the reference image using any one of a current partial fingerprint image and a previous partial fingerprint image as a target image and the other as a reference image. Fingerprint recognition method characterized in that obtained through. The method of claim 7, wherein the relative sliding information between the partial fingerprint images includes a search slice set in one of a current partial fingerprint image and a previous partial fingerprint image, and a reference slice set in the other one. Fingerprint recognition method characterized in that obtained through the comparison between slices. The fingerprint recognition method according to claim 7, wherein the relative sliding information between the partial fingerprint images is obtained by comparing brightness values of overlapping image regions between two adjacent partial fingerprint images. The method of claim 12, wherein the sliding direction and the speed are calculated by calculating, in pixels, the relative degree of movement in the long axis and short axis of the target image when the difference in the brightness values of the overlap regions is minimized based on the reference slice image. Fingerprint recognition method characterized in that. The fingerprint recognition method according to claim 12, wherein the reference slice image has a fixed position and size in the reference image or a variable adjustment of the position and size. 12. The fingerprint of claim 11, wherein the reference image and the target image are adjusted by applying the same gain to all areas of the image so that the average brightness value is the same before the sliding speed and the direction search. Recognition method. 8. The fingerprint recognition method according to claim 7, wherein the fingerprint ridge information is divided into partial fingerprint images in block units and extracted by referring to the distribution of fingerprint ridges in each block. The method of claim 7, wherein the matching of the partial fingerprint images is performed by calculating a degree of movement of the entire fingerprint image to be matched, extracting optimal fingerprint movement information, and collectively extracting partial fingerprint images using sliding direction and speed information. Fingerprint recognition method characterized in that the matching. The fingerprint ridge information amount of the entire fingerprint image to be matched is obtained by calculating and accumulating the fingerprint ridge information amount of ROI pixels included in each partial fingerprint image by predicting relative speed and direction information of each partial fingerprint image. Fingerprint recognition method characterized in that. The overlapping region of claim 7, wherein the optimal movement information of the entire fingerprint image to be matched is superimposed on the entire fingerprint image to be matched with a given matched image size based on the predicted fingerprint ridge information amount and the position information of the ROI pixels. And calculating the relative degree of movement with respect to the reference position of the given matched image by finding a point where the maximum amount of information is obtained. The method of claim 7, wherein each partial fingerprint image is matched to the entire registration image only in an area excluding an overlapping portion with the partial fingerprint image to be matched later by using sliding speed and direction information of adjacent partial fingerprint images. Fingerprint recognition method characterized in that. Acquiring a fingerprint image sequentially and partially continuously according to sliding of a user; Storing the acquired partial fingerprint images; Detecting relative sliding directions and speeds between adjacent partial fingerprint images based on a comparison of brightness values between the consecutive partial fingerprint images as one reference image and the other as a target image; Skew sliding detection method of the fingerprint recognition system, characterized in that. The method of claim 21, wherein the comparing of brightness values between the overlapping images comprises: setting a portion of a long axis direction of a reference image as a reference slice region and a portion of a target image as a target slice region; Superimposing a target image on a reference image while moving the target image in a long axis and a short direction; Searching for a point at which the difference in brightness between the pixels of the target image one-to-one overlapping the reference slice region and the pixels of the reference slice image is the minimum; And calculating relative sliding directions and speeds based on the position information between the retrieved points. Skew sliding detection method of the fingerprint recognition system comprising a.

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