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Automatic fingerprint identifying technique under verification mode

A verification mode and fingerprint recognition technology, applied in the field of biometric identification, can solve the problems of incomplete refinement and low adaptability of fingerprint images, and achieve the effect of ensuring accuracy and eliminating burrs.

Inactive Publication Date: 2005-11-30
NANJING UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] (1) In order to solve the problem of incomplete thinning and the existence of a large number of burrs in the existing fingerprint thinning technology, this technology proposes a new template thinning method, which realizes the fingerprint image thinning Complete and thorough refinement, and to a large extent eliminate the occurrence of glitches, thus ensuring the accuracy of subsequent feature extraction and recognition
[0016] (2) In order to solve the problem that the existing fingerprint ridge direction extraction technology has low adaptability to fingerprint image quality, this technology proposes a new method for fingerprint ridge direction extraction based on the idea of ​​multi-level segmentation

Method used

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  • Automatic fingerprint identifying technique under verification mode
  • Automatic fingerprint identifying technique under verification mode
  • Automatic fingerprint identifying technique under verification mode

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Embodiment 1. Thinning processing for two cases of incomplete thinning (not single-pixel width) at the bifurcation point in Fig. 6

[0054] For the situation shown in Figure 6(a), it can be found that the point in the third row and the second column (the row is horizontal and the column is vertical) is a redundant pixel, and deleting it does not affect the connectivity of the lines, it should be deleted . So we can build a elimination template for this point (as shown in Figure 10(a)), and if a certain part of the image conforms to the elimination template, set the gray background point in the middle of the template to 0 (as shown in Figure 10(a) b) shown). The situation at the bifurcation point before and after treatment is shown in Fig. 10(c), (d), respectively. It can be seen that after processing, the bifurcation point satisfies the single-pixel width. Considering the factor of rotation, there should be 4 templates in total (Fig. 7a-d).

[0055] For the situatio...

Embodiment 2

[0056] Embodiment 2 refines processing to burr phenomenon

[0057] In view of the occurrence of burrs, after our research, we found that the appearance of burrs is very sensitive to the direction of the lines. When the direction angle of the lines is in the second quadrant, burrs are prone to appear, especially when the lines are approximately horizontal and vertical. obvious. Moreover, the burrs are basically in the upward, leftward, and rightward directions, that is, the directions of 90 degrees, 180 degrees, and 0 degrees. Therefore, we believe that the generation of burrs is related to the incomplete symmetry of the template.

[0058] In order to explain more clearly, two pictures are given to illustrate. As shown in Figure 12, Figure 12(a) is the binarized image before thinning, and Figure 12(b) is the image after thinning. Obviously, burrs are generated in the lines after thinning. Now analyze the refinement process in detail to explain the cause of the burr. The or...

Embodiment 3

[0062] Embodiment 3 Fingerprint Line Direction Information Extraction Method

[0063] First of all, this extraction method adopts the method of multi-level segmentation. Specifically, a fingerprint image to be processed is divided into three-level block fingerprints according to the block sizes of 8×8, 16×16, and 32×32. image, and then calculate the directional flow information of the fingerprint image for the fingerprint image under each level of block size, and finally integrate the ridge direction information calculated under the multi-level block size, and divide them into blocks according to the large level The direction information of the size smoothes the direction information of the small-level block size, so as to finally extract relatively accurate and reliable fingerprint line direction information.

[0064] Let D32[i][j], D16[m[n], and D8[r][s] denote the ridges of the block image obtained under the block sizes of 32×32, 16×16, and 8×8, respectively direction, the...

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Abstract

The invention discloses a kind of automatic fingerprint recognition technology under confirmation pattern, especially points to the problem that the picture has bifurcation which is not thinned completely and has burrs after the improved OPTA algorithm is thinned. The incomplete thin is caused by incomplete eliminating of template, thus the invention constructs eliminate template and the retention template to process the situation. The burr is generated by the asymmetry of retention template, thus, on base of the 6 retention templates of improved OPTA algorithm, reduces the templates which have upwards, leftwards and rightwards burrs, and eliminates the burrs. The invention also proposes a new method for withdrawing the fingerprint picture direction information with multistage division.

Description

1. Technical field [0001] The invention relates to the field of biological identification, in particular to an automatic identification method for finger prints. 2. Background technology [0002] The automatic fingerprint identification method refers to a biometric identification method that uses the distribution pattern of ridges and valleys on the surface of the finger to confirm the identity of the identified object. Human fingerprints are innate and determined during the fetal period. Human beings have used fingerprints as a means of identification for a long time, and the legitimacy of using fingerprints for identification has long been widely recognized. [0003] Generally speaking, automatic fingerprint identification methods are divided into two types: verification mode and identification mode. The verification mode is also called the 1:1 mode, which is to judge whether you are the person you said; the identification mode is also called the 1:N mode, which is to ju...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
Inventor 宁新宝詹小四谭台哲尹义龙黄峥杨照忠王业琳骆峰杨小冬
Owner NANJING UNIV
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