Fingerprint texture image denoising enhancing method and system

Abstract

The invention relates to a fingerprint texture image denoising enhancing method. According to the method, a non-local diffusion tensor diffusion-fluctuation partial differential equation model is provided. The method comprises the following steps that an image is preprocessed; the non-local structure tensor is calculated; the non-local diffusion tensor is calculated through the non-local structure tensor; iteration updating is carried out, and a result image is obtained. The texture characteristic can be enhanced while the noise is eliminated, a certain repairing function of the fracture texture is achieved, and the fingerprint recognition can be carried out more accurately in the later process.

Description

technical field [0001] The invention belongs to the technical field of image preprocessing, and in particular relates to a method for denoising and enhancing a fingerprint texture image and a system thereof. Background technique [0002] Fingerprint recognition technology has become one of the most mature and convenient biometric technologies due to its advantages of high stability, uniqueness, high reliability, easy collection, and difficult to forge and decipher, and it is widely used in security, public security, IT, finance, Widely used in medical and other industries. [0003] In the actual fingerprint collection process, due to the influence of the performance of the collection equipment, the collection environment, and the state of the finger of the person being collected, there are usually various noises in the fingerprint image, which will greatly affect the subsequent feature extraction and recognition. error. Therefore, the preprocessing of fingerprint images is...

AI Technical Summary

Problems solved by technology

Frequency-domain filtering methods, such as Fourier transform, wavelet transform, etc., all achieve noise removal by filtering out the high-frequency part of the image, but the edge and texture structure information that also has high-frequency characteristics in the image will inevitably be lost; the spatial domain Medium-sampled local template filtering or non-linear diffusion model filtering method can be adaptively enhanced according to the local characteristics of the image, but it is susceptible to noise interference

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