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大库容量指纹自动识别系统中的优化模型与算法

郭田德1,2  韩丛英1,2,*  赵彤1,2   阿勇3  吴敏1,3  白超超4  唐思琦1   

  1. 1. 中国科学院大学数学科学学院, 北京 100049 2. 中国科学院大数据挖掘与知识管理重点实验室, 北京 100190
    3. 北京东方金指科技有限公司, 北京 100190 4. 中国科学院大学计算机与控制学院, 北京 100049
  • 收稿日期:2017-08-27 出版日期:2017-12-15 发布日期:2017-12-15
  • 通讯作者: 韩丛英 hancy@ucas.ac.cn
  • 基金资助:

    国家自然科学基金(Nos. 11331012, 11731013, 11571014)

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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摘要：

生物学研究表明, 指纹在胎儿时期发育形成, 并且其脊线结构在人的一生中从不改变, 除非当指尖处深度擦伤之类的事故发生而导致指纹损伤. 指纹的这种特性使得指纹作为生物特征进行身份认证非常有吸引力. 指纹自动识别系统包括指纹图像的获取和存储、指纹图像数据的再表达和特征提取、指纹分类和索引、指纹匹配等模块. 针对大库容量指纹自动识别系统各个模块中的一些关键技术, 建立了最优化模型, 设计了快速准确的求解算法, 使得指纹自动识别系统的各项指标均能够达到国际先进水平, 并应用到我国一些省市和公安部刑侦领域指纹自动识别系统中.

关键词: 大库容量, 指纹, 自动识别系统, 优化模型

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