Earticle

초록

영어

Most of the existing fingerprint retrieval systems are based on the overall characteristics and detailed features of fingerprints, and their performance is poor in the cases of low-quality fingerprint images, such as incomplete fingerprint images. In order to improve the recognition speed, accuracy, and robustness of automated fingerprint recognition systems based on large-scale fingerprint databases, in this paper, we propose a fast fingerprint classification retrieval and identification method based on Scale Invariant Feature Transform (SIFT) and Local Sensitive Hash (LSH) algorithms. A method based on scale space theory extracts SIFT feature point descriptors of relatively high-quality fingerprint images in accordance with the principle of a greater matching contribution rate, uses multi-template image feature fusion technology to build a stable fingerprint feature template database, achieves the storage and retrieval of high-dimensional SIFT features using the LSH algorithm, and carries out matching progressively by level on the basis of SIFT’s matching principle of close neighboring priority scale. Experimental results show that the proposed method has strong penetration, high retrieval efficiency, good recognition accuracy, and strong robustness, thereby providing a fast and efficient retrieval and matching mechanism for the automated recognition of the large-scale fingerprint database, with strong practicality.

목차

Abstract
 1. Introduction
 2. SIFT Features Representation of Fingerprint Image
  2.1. Brief Description of SIFT
  2.2. Brief Description of SIFT
  2.3. SIFT Adjacent Scale Priority Principle for Fingerprint Matching
  2.4. SIFT Adjacent Scale Priority Principle for Fingerprint Matching
 3. LSH Retrieval and Matching
  3.1. LSH
  3.2. Retrieval Process
  3.3. Matching Strategy
 4. Experiment Results and Performances Analysis
  4.1. Retrieval Performance
  4.2. Matching Performance
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Yunfei Zhong [ School of Information Science and Engineering, Central South University, Changsha 410083, China, School of Packaging Materials and Engineering, Hunan University of Technology, Zhuzhou 412007, China ]
• Xiaoqi Peng [ School of Information Science and Engineering, Central South University, Changsha 410083, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605