Improvement Research On The Related Algorithm Of Fingerprint Identification

Application of the fingerprint of human history began in the ancient. Fingerprint identification is the oldest, as early as 6000 years ago, will use fingerprints to replace the human signature. Archaeologists confirmed that, as early as the late primitive society, the fingerprint as identification tool has been applied in China.While fingerprints are widely used in ancient China, but this application is only an emotional application, not on the basis of this synthesis and inductive reasoning and did not rise to the science and application of theory. With the social development and scientific and technological progress, the people of fingerprint pattern recognition system, more and more in-depth research, and have made tremendous progress. Many enterprises and schools such as the introduction of the fingerprint attendance system, but the current time and attendance system in recognition speed and accuracy are still some problems, and therefore requires us to fingerprint pattern recognition algorithms to do further study.In this paper, research on fingerprint recognition technology in learning rough home and abroad, is studied based on the fingerprint pattern recognition system algorithm. Mainly contains: fingerprint image preprocessing,fingerprint feature extraction and fingerprint matching.In the thesis the development of fingerprint pattern recognition at home and abroad was summarized in detail, fingerprint binarization algorithm and fingerprint pattern character matching algorithm were further investigated based on previous theory in order to improve the processing speed and performance of fingerprint pattern recognition algorithm. Firstly, as binary algorithm had poor anti-noise properties and difficulties in selecting suitable threshold value, a new binarized gray threshold segmentation method, which combined local adaptive and fingerprints grayscale image information and had and the characteristics of less calculation and preferable antijamming, was come up. Then based on genetic algorithm a new re-matching algorithm, of which the detail screening part was figured out by a new mothod of building irrelevant transform structure information and the coordinates calibration part was settled by polar coordinates, was put forward. Then an adjustable Bounding Box is used to process the calibrated feature points. Finally, it was proved by comparing the finger images in the FVC2004 fingerprints database with the images obtained by classic finger print pattern matching algorithm that this algorithm was feasible.