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Method for segmenting fingerprint image based on cellular neural network and morphology

A fingerprint image and neural network technology, applied in the field of image processing, can solve the problems of high computational complexity of the algorithm model and the wrong segmentation rate of low-quality fingerprint images, and achieve smooth and complete contours.

Inactive Publication Date: 2011-11-23
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0009] The above fingerprint segmentation algorithm is based on the pixel value information and block information of the fingerprint image, and the methods (1) and (2) consider too few factors, so the segmentation of low-quality fingerprint images will produce a large error segmentation rate; (3) and (4) although various factors have been considered, the computational complexity of the algorithm model is too high

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  • Method for segmenting fingerprint image based on cellular neural network and morphology
  • Method for segmenting fingerprint image based on cellular neural network and morphology
  • Method for segmenting fingerprint image based on cellular neural network and morphology

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Embodiment Construction

[0052] The method of the present invention is implemented in VC6.0 software, and the fingerprint image is obtained by a CMOS pressure-sensitive sensor. The average time to complete a 480×640 fingerprint image segmentation in PC Intel Celeron 2.0GHZ with VC6.0 is 0.03s.

[0053] A specific implementation example of the present invention is given below.

[0054] It should be noted that the parameters in the following examples do not affect the generality of this patent.

[0055] 1. Collect the original fingerprint image, and calculate the gray histogram of the original image.

[0056] 2. Calculate the fuzziness of the fingerprint image by using the initial threshold obtained from the gray histogram.

[0057] 3. Calculate the entropy of fingerprint image fuzziness with Shannon function, and calculate the optimal fuzzy threshold by taking the minimum value of entropy.

[0058] 4. Calculate the neural cell network threshold with the optimal fuzzy threshold, and use two 3×3 squar...

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Abstract

The invention discloses a method for segmenting a fingerprint image based on a cellular neural network and morphology and belongs to the technical field of image processing. The method comprises the following steps of: firstly, determining an initial threshold value t in a curve trough between a fingerprint foreground peak value and a background peak value of a gray histogram h(k) of an initial fingerprint image, and computing the fuzziness mu(f(x, y)) of the initial fingerprint image; secondly, computing an entropy E(I) of the fuzziness by using a Shannon function S(mu(f(x, y))), and minimizing the entropy and computing an optimum fuzzy threshold value t*; thirdly, computing a threshold value z* of the cellular neural network by using the optimum fuzzy threshold value t*, and processing the fingerprint image by using two 3*3 square cellular neural network templates to obtain a substantial fingerprint foreground area image; and finally, performing morphological operation on the substantial fingerprint foreground area image by using a 9*9 morphological template to obtain a final fingerprint foreground area image. The method has the advantages that: computation quantity is relatively lower; and the contour of a fingerprint foreground subjected to the morphological operation is relatively smoother.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to the fingerprint image processing technology in the fingerprint identification technology. Background technique [0002] Biometric identification technology is a solution that uses automatic technology to measure its physical characteristics or individual behavior characteristics for identity verification, and compares these characteristics or characteristics with the template data in the database to complete identity authentication. As the most mature and convenient member of biometric technology, fingerprint recognition technology has been successfully applied in various fields of society. Such as: access control, attendance system, e-commerce, ATM automatic teller machine and criminal identification system, etc. As a safe and reliable identification method, the fingerprint automatic identification system established by relying on fingerprint identification technology,...

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Application Information

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IPC IPC(8): G06K9/34G06K9/00G06N3/02
Inventor 解梅胡姣姣
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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