Fingerprint Image Preprocessing And Improved Algorithm,

AFIS(Automated Fingerprint Identification System) is started from 1960's, it has replaced conventional method to recognize fingerprints with computers. APIS is applied in daily life more and more with the development of computer technology, the appearance of cheap collector and the effective algorithms. APIS is becoming the research center of academic and commerce. It is superior to the other biological feature with its special virtues; the most important is its practicability and feasibility. It has been considered the main method of the biological feature recognition in the future.The preprocessing and feature recognition of APIS based on minutia features are discussed in this paper. After the research and the comparisons on the exist algorithms, some new algorithms are proposed.The preprocessing is the first step of APIS, it is the most important step. It includes Filter, Orientation, Binarization, Thinning and so on.The least mean square is used to get the blocks orientation; get the binary image with the binarization method of fingerprint images based on orientation and dynamic threshold; in the thinning, an improved thinning algorithm is proposed here in order to overcome the shortages of the existing thinning algorithms, the new templates can significantly reduce the scanning iterations and speed up the thinning process while keeping the same thinning results; the image parallel thinning algorithm for serial computer is suitable for all kinds of parallel template thinning algorithms, it improve the computation efficiency of image parallel thinning on serial computers based on a coding scheme for each 4x4 binary pixels; in the features extraction, the center of fingerprint is defined as the point where the curvature on ridge is maximum, so the definition of the center of fingerprint is unified.All algorithms are implemented on PC by VC++. The results are given in the paper demonstrate that the new methods can enhance processing effects of fingerprint images.