A novel ant colony optimization algorithm for large-distorted fingerprint matching
文献类型：期刊论文
| 作者 | Cao, Kai1; Yang, Xin2 ; Chen, Xinjian3; Zang, Yali2; Liang, Jimin1; Tian, Jie1,2
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| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2012 |
| 卷号 | 45期号:1页码:151-161 |
| 关键词 | Distortion Fingerprint matching Minutiae pairing Minutia similarity Ant colony optimization |
| 英文摘要 | Large distortion may be introduced by non-orthogonal finger pressure and 3D-2D mapping during the process of fingerprint capturing. Furthermore, large variations in resolution and geometric distortion may exist among the fingerprint images acquired from different types of sensors. This distortion greatly challenges the traditional minutiae-based fingerprint matching algorithms. In this paper, we propose a novel ant colony optimization algorithm to establish minutiae correspondences in large-distorted fingerprints. First, minutiae similarity is measured by local features, and an assignment graph is constructed by local search. Then, the minutiae correspondences are established by a pseudo-greedy rule and local propagation, and the pheromone matrix is updated by the local and global update rules. Finally, the minutiae correspondences that maximize the matching score are selected as the matching result. To compensate resolution difference of fingerprint images captured from disparate sensors, a common resolution method is adopted. The proposed method is tested on FVC2004 DB1 and a FINGERPASS cross-matching database established by our lab. The experimental results demonstrate that the proposed algorithm can effectively improve the performance of large-distorted fingerprint matching, especially for those fingerprint images acquired from different modes of acquisition. (C) 2011 Elsevier Ltd. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | IMAGE-ENHANCEMENT ; MINUTIAE ; SYSTEM ; VERIFICATION ; MODEL |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000295760700013 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/4107]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 作者单位 | 1.Xidian Univ, Life Sci Res Ctr, Sch Life Sci & Technol, Xian 710071, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.NIH, Radiol & Imaging Sci Dept, Ctr Clin, Bethesda, MD 20892 USA |
| 推荐引用方式 GB/T 7714 | Cao, Kai,Yang, Xin,Chen, Xinjian,et al. A novel ant colony optimization algorithm for large-distorted fingerprint matching[J]. PATTERN RECOGNITION,2012,45(1):151-161. |
| APA | Cao, Kai,Yang, Xin,Chen, Xinjian,Zang, Yali,Liang, Jimin,&Tian, Jie.(2012).A novel ant colony optimization algorithm for large-distorted fingerprint matching.PATTERN RECOGNITION,45(1),151-161. |
| MLA | Cao, Kai,et al."A novel ant colony optimization algorithm for large-distorted fingerprint matching".PATTERN RECOGNITION 45.1(2012):151-161. |
入库方式： OAI收割
来源：自动化研究所
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