中文

Operations Research Transactions ›› 2017, Vol. 21 ›› Issue (4): 19-33.doi: 10.15960/j.cnki.issn.1007-6093.2017.04.002

Special Issue: 第五届中国运筹学会科学技术奖获奖者专辑

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Optimization models and algorithms for large capacity fingerprint automatic identification system

GUO Tiande1,2  HAN Congying1,2,*   ZHAO Tong1,2 A Yong3  WU Min1,3  BAI Chaochao4  TANG Siqi1   

  1. 1. School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China 2. Key Laboratory of Big Data Mining Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China 3. Bejing Eastern Golden Finger Technology Co.Ltd., Beijing 100190, China 4. School of Computer and Control Engineering, University of  Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-08-27 Online:2017-12-15 Published:2017-12-15

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Abstract:

Biological studies have shown that fingerprints' ridge structure never changes throughout the life of an individual after they are fully formed at about 7 months of fetus development except due to accidents such as bruises and cuts on the fingertips. This characteristic makes fingerprints very attractive for biometric authentication. Automatic fingerprint identification system (AFIS) includes the acquisition and storage of fingerprint images, the representation and feature extraction, fingerprint classification and indexing, fingerprint matching and other modules. Aiming at some key technologies in each module for the large capacity of AFIS, we established optimization models, designed fast and accurate algorithms. Experimental results showed that our algorithms are robust and effective. AFIS embedded in our core algorithms has been applied to criminal investigation areas in some provinces and cities in China.

Key words: large capacity, fingerprint, automatic identification system, optimization models