Deformed fingerprint identification method based on local triangle structure characteristic collection

Abstract

This invention relates to an identifying method for deformed fingerprints based on local triangle structure character set, on the basis of the character that relative deformation of fingerprint image is limit in local regions, which expresses fingerprints with a fuzzy character-local triangle structure character sets to convert the computation to integral similarity among fingerprints to similarity balance among character sets, first of all, which puts forward a fuzzy measurement method of similarity between two triangle structures then further makes up of a character vector composed of local similarities of all triangle structures then to map the pair of similarity vectors to a normalized number in the region of [0, 1] to quantize the integral similarity among fingerprint images to further get the matched result.

Description

technical field [0001] The invention belongs to the field of biometric feature recognition, relates to frontier knowledge such as image processing, pattern recognition, and computer technology, and particularly relates to realizing the recognition of non-linearly deformed fingerprint images by using local feature information and a fuzzy similarity measurement method. Background technique [0002] At present, the development of biometric identification technology has made fingerprint identification technology more and more mature, and it has been fully practical at present. Due to the sharp drop in the price of automatic fingerprint identification systems, the application of automatic fingerprint identification is no longer limited to the fields of law and public security. It can be used as a means for computers to confirm users, as an information security technology for accessing network resources, and can also be used for confirmation of bank ATM cards and credit cards, dou...

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Problems solved by technology

But applying this model to "correct" the fingerprints to be matched results in two fingerprints becoming more similar regardless of whether they are from the same finger or not

[0008] Based on the above analysis and research, we found that the current research on the matching of nonlinear deformation fingerprints only focuses on finding and describing local registration, but does not consider the rationality of the global "registration mode" formed by these local matches.

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