Earticle

초록

영어

Fingerprint-based recognition systems have been widely deployed in numerous civilian and government applications. However, the fingerprint recognition systems can be deceived by commonly used sensors with the artificially fake fingerprint made using materials like gelatin or silicon. In this paper, spoof fingerprint detection is considered as a two-class classification problem and co-occurrence matrix is constructed from image gradients to extract features. In feature extraction process, the quantization operation is firstly applied with the fingerprint images. Secondly, the horizontal and vertical differences at each pixel are calculated. Thirdly, the differences of large absolute values are truncated into a reduced range. Finally, the co-occurrence matrix is constructed from the truncated differences, and the elements of the co-occurrence matrix are directly used as features. The features are separately utilized to train support vector machine classifiers on two databases. The experimental results have demonstrated that the proposed method outperform the state-of-the-arts.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Feature Extraction Process
  3.1. Quantization
  3.2. Differences and Truncation
  3.3. Co-occurrence Matrix
 4. Experiments
  4.1. Databases and Evaluation Criterion
  4.2. Support Vector Machine (SVM)
  4.3. Selection of Parameters
  4.4. Comparison with Previous Methods
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Yujia Jiang [ College of Architecture and Artistic Design, Hunan Institute of Technology, Hengyang, 421001, China ]
• Xin Liu [ College of Architecture and Artistic Design, Hunan Institute of Technology, Hengyang, 421001, 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