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People rely on physiological characteristics and behavioral characteristics of the person's own body authentication and identification technologies collectively known as biometric identification technology. The characteristics of the people who have applied include: fingerprint, face, iris, palm prints, gait, speech, etc., as the earliest use of biometric technologies including fingerprint identification technology, because of its high recognition accuracy makes fingerprint recognition technology to become one of the most representative of today's biometric technology. Automated fingerprint identification technology is a high-tech sensor technology, bio-technology, digital image processing, pattern matching, electronic technology in one. In recent years, fingerprints, biometric identification technology has become a hot research at home and abroad, and is widely used. Nowadays, automatic fingerprint recognition technology has been applied field of public security, customs, banking, access control, access, time and attendance needs to authenticate. With the further development of the network, automatic fingerprint identification technology provides a solution to the network and database security and confidentiality issues. After years of effort, the Automated Fingerprint Identification research has made great progress, but, so far, the automatic fingerprint recognition technology there are still a lot of need to improve and perfect place. In this paper, the system analysis based on fingerprint recognition technology Research, two key technology for a more in-depth study of the fingerprint image thinning and fingerprint ridge distance estimation. Text is divided into five chapters, the first chapter is an introduction; Chapter II is the fingerprint thinning algorithm research; Chapter III is based on the spectral analysis of the fingerprint ridge distance estimation; Chapter IV is based on the regional level ridge distance estimation ; last chapter is a summary. The thesis studies include the following aspects: (1) the fingerprint image refinement algorithm. Refined as a critical step in fingerprint identification, fingerprint recognition effect great influence, in order to study the thinning algorithm, we realized two commonly used fingerprint refinement algorithm ---- fast thinning algorithm and improved The the OPTA algorithm is, and on this basis, the analysis of the strengths and weaknesses of the two algorithms, and improved OPTA algorithm to further improve. An integrated thinning algorithm: OPTA algorithm combined with the use of fast thinning algorithm and improved. Experimental results show that the integrated refinement algorithm can achieve better refining effect.
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