Research On Preprocessing Of Fingerprint Image

In recent years, biological features have been widely used in the field of personal identification with the development of computer technology and artificial intelligent technology, in that they have the advantages of uniqueness, stability, higher security and portability. Compared to other biometric identification methods fingerprint identification not only has the security advantages, but also has higher stability, practicality and feasibility. So it is widely used in social security, financial security, company attendance, entrance control, airport, customs and other fields.A complete set of fingerprint recognition algorithm generally includes three steps: image preprocessing, feature extraction and feature matching. As the basis of feature extraction and matching, the preprocessing on fingerprint images can reduce the noise and improve the clearance of fingerprint ridge, so the result of preprocessing can severely affect the accuracy of identification system. Currently, researchers have proposed many methods for fingerprint image preprocessing, but the processing results of images with low quality are not ideal. Therefore, the fingerprint image preprocessing algorithm is still a hot research field of biometric identification.By summarizing and digesting the existing researching, this paper focuses on the fingerprint image preprocessing algorithms including image segmentation, enhancement, binarization and thinning. This article mainly completes the following works:(1) In the step of fingerprint segmentation:firstly, we introduce the image normalization algorithm to transform the gray scale, in order to provide unified specifications for behind steps. Then we compare the advantages and disadvantages of the segmentation algorithm based on variance and its gradient and the algorithm based on orientation coherence. Finally, we propose a new segmentation algorithm and experimented to prove the algorithm can achieve ideal segmentation results.(2) In the step of fingerprint enhancement:firstly, we describe the most common methods for getting orientation and frequency field of fingerprint image, and then discuss the Gabor filter based fingerprint enhancement algorithm and introduced the separable Gabor filter based algorithm. Finally, in order to shorten the processing time, we propose an improved method on the basis of the separable Gabor filter based algorithm,(3) In the step of fingerprint binarization:We discuss the binarization algorithm based on fixed threshold and the one based on orientation information. Then a combined binarization method is proposed according to the advantages and disadvantages of the two above methods. At last, a post-processing method is introduced.(4) In the step of fingerprint thinning:Firstly, we discuss the disadvantages of quick thinning algorithm and improved OPTA thinning algorithm. Then we introduce an index thinning algorithm based on eight neighborhood points and experimented to prove the algorithm can achieve ideal thinning results.Finally, the major findings of the study are summarized and limitations are pointed out to give the directions of future work.