Fingerprint epipole accurate positioning method based on image spatial domain characteristic

Abstract

The invention discloses a fingerprint epipole accurate positioning method based on an image spatial domain characteristic. The method comprises the following concrete steps: solving a pixel-grade direction field O of a fingerprint image by use of a gradient method; extracting each coarse epipole position in the direction field O by use of a Poincare index method; calculating a binary image I of the fingerprint image by use of a short time Fourier transform method; inputting the direction field O, the coarse epipole positions and the binary image I into a bifurcation aggregation extraction module, and extracting all bifurcation points fc and aggregation points gh within an a*b rectangular scope nearby the coarse epipole positions for storing in a matrix FJi; inputting the matrix FJi into a denoising module to remove all pseudo bifurcation points and pseudo aggregation points of the matrix FJi so as to obtain a matrix FJi<->; inputting the matrix FJi<-> obtained after denoising into an arc extraction module to obtain all arcs, and storing the obtained arcs in a matrix Hu; and inputting the matrix Hu into a precision positioning module to obtain a final result of epipole positioning. According to the invention, spatial domain information of the fingerprint image is utilized, and the detection precision is improved while the epipole detection consistency is maintained.

Description

technical field [0001] The invention belongs to the technical field of biological feature identification and information security, and in particular relates to a precise positioning method of fingerprint core points based on image space features. Background technique [0002] Due to the inherent characteristics of biometrics (fingerprint, iris, face, etc.), biometric identification technology makes it possible to surpass and replace traditional identification technology, and has begun to be promoted in specific application fields in some countries and regions and use. Among them, fingerprint recognition has reached a good balance in various indicators of identity recognition, such as universality, uniqueness, collectability, user acceptance, etc., making it a research hotspot; in addition, fingerprint collection equipment is mature in technology and low in price. As well as the advantages of low space requirements for the storage of fingerprint templates, it occupies a domi...

AI Technical Summary

Problems solved by technology

For the existing fingerprint recognition technology, most singular point detection methods are based on the block-level direction field, so the accuracy and consistency of the detected singular points are limited by the size of the block. Accurately locate the singular point to a certain pixel; second, when two singular points are very close to each other (in the same block), there will be missed detection

For the subsequent identification, it will bring two main problems: first, reduce the efficiency of the fingerprint image alignment method based on the singular point; second, increase the error rate of the fingerprint classification method

[0004] At present, there is no research on the precise positioning of nuclear points based on the spatial information of fingerprint images in the published literature.

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