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Iris geometrical property extracting method based on property edge distribution

A feature edge and geometric feature technology, applied in the field of iris geometric feature extraction based on feature edge distribution, can solve the problems of unsatisfactory recognition accuracy, algorithm performance easily affected by the external environment, and good anti-interference

Inactive Publication Date: 2005-09-28
上海邦震科技发展有限公司
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Problems solved by technology

The algorithms of Daugman[1], [2] and Wildes[3] have high recognition accuracy for high-quality iris images, but the algorithm performance is easily affected by the external environment; the algorithm of Boles[4] has relatively low requirements for the quality of iris images. Good anti-interference, but the recognition accuracy is not ideal

Method used

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  • Iris geometrical property extracting method based on property edge distribution
  • Iris geometrical property extracting method based on property edge distribution
  • Iris geometrical property extracting method based on property edge distribution

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Embodiment Construction

[0060] The present invention is further described below by way of examples.

[0061] (1) Divide iris sub-regions.

[0062] First, normalize the iris image to obtain a rectangular iris texture image, such as Figure 9 , and divide the rectangular iris texture image into subregions, such as Figure 10 , to complete the iris image divided into sub-regions. Each iris texture sub-region is a minimum extraction unit of iris geometric features for feature matching.

[0063] (2) Using arcsine wavelet to extract edges.

[0064] Such as Figure 11 (a), for the 256-color iris original image without edge extraction, use Asbw9.9 as the wavelet basis function to perform multi-resolution edge extraction, resolution level i=-1,-2,-3,-4 ;Such as Figure 11 (b), an edge image generated for a set of edge pixels at four resolution levels, the image contains geometric edge information at each resolution; as Figure 11 (c) is the result of directly thresholding the edge pixel gradient modulu...

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Abstract

The present invention belongs to the field of biological characteristic distinction, and is especially the method of extracting geometric characteristic of iris based on characteristic edge distribution. The method includes first defining geometric characteristic of iris and describing its reliability and stability; subsequent extracting geometric characteristic edge of iris in antisymmetric double orthogonal wavelet process and constituting overall edge distribution characteristic in unequal interval grading according to the inhomogeneous distribution of geometric characteristic of iris; and finally introducing characteristic distance expression and proposing legal user judging method. The method has high distinction precision and less outer factor influence.

Description

technical field [0001] The invention belongs to the technical field of biological feature recognition, and in particular relates to an iris geometric feature extraction method based on feature edge distribution. Background technique [0002] The biometric identification technology derived from the intersection of biotechnology and information technology is an emerging interdisciplinary subject. Among various biometrics (such as fingerprint, iris, face, gait), the iris is representative. [0003] Classical iris feature extraction algorithms are all based on iris texture features. The algorithms of Daugman[1], [2] and Wildes[3] have high recognition accuracy for high-quality iris images, but the algorithm performance is easily affected by the external environment; the algorithm of Boles[4] has relatively low requirements for the quality of iris images. The anti-interference is good, but the recognition accuracy is not ideal. Contents of the invention [0004] The purpose ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/48
Inventor 宫雅卓沈文忠
Owner 上海邦震科技发展有限公司
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