一个利用模糊匹配算法的指纹识别系统（外文文献翻译）.docVIP

A Fingerprint Recognizer Using Fuzzy Evolutionary Programming Abstract A fingerprint recognizing system is built with two principal components: the fingerprint administrator and the fingerprint recognizer. Fingerprints are identified by their special features such as ridge endings, ridge bifurcation, short ridges, and ridge enclosures, which are collectively called the minutiae. The fingerprint administrator uses the method of gray scale ridge tracing backed up by a validating procedure to extract the minutiae of fingerprints. The fingerprint recognizer employs the technique of fuzzy evolutionary programming to match the minutiae of an input fingerprint with those from a database. Experimental results show the methods used are highly effective. 1. Introduction Fingerprints have been used for many centuries as a means of identifying people [8,16]. As it is well known that fingerprints of an individual are unique and are normally unchanged during the whole life, the use of fingerprints is considered one of the most reliable methods of personal verification. This method has been widely used in criminal identification, access authority verification, financial transferring confirmation, and many other civilian applications. In the old days, fingerprint recognition was done manually by professional experts. But this task has become more difficult and time consuming, particularly in the case where a very large number of fingerprints are involved. During the past decade, several automatic fingerprint identification systems have been made available to meet the demand of new applications [7,16,20,30]. The methods used in these systems are still far from complete satisfaction, however, due to inaccurate extraction of fingerprint characteristics and ineffective pattern matching procedures, which are the two major tasks of fingerprint identification. The Federal Bureau of Investigations method of identifying a fingerprint by its set of minutiae is widely used in automatic finge