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  • 标题:A Novel 2D Feature Extraction Method for Fingerprints Using Minutiae Points and Their Intersections
  • 其他标题:A Novel 2D Feature Extraction Method for Fingerprints Using Minutiae Points and Their Intersections
  • 本地全文:下载
  • 作者:Nibras Ar Rakib ; SM Zamshed Farhan ; Md Mashrur Bari Sobhan
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2017
  • 卷号:7
  • 期号:5
  • 页码:2547-2554
  • DOI:10.11591/ijece.v7i5.pp2547-2554
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:The field of biometrics has evolved tremendously for over the last century. Yet scientists are still continuing to come up with precise and efficient algorithms to facilitate automatic fingerprint recognition systems. Like other applications, an efficient feature extraction method plays an important role in fingerprint based recognition systems. This paper proposes a novel feature extraction method using minutiae points of a fingerprint image and their intersections. In this method, initially, it calculates the ridge ends and ridge bifurcations of each fingerprint image. And then, it estimates the minutiae points for the intersection of each ridge end and ridge bifurcation. In the experimental evaluation, we tested the extracted features of our proposed model using a support vector machine (SVM) classifier and experimental results show that the proposed method can accurately classify different fingerprint images.
  • 其他摘要:The field of biometrics has evolved tremendously for over the last century. Yet scientists are still continuing to come up with precise and efficient algorithms to facilitate automatic fingerprint recognition systems. Like other applications, an efficient feature extraction method plays an important role in fingerprint based recognition systems. This paper proposes a novel feature extraction method using minutiae points of a fingerprint image and their intersections. In this method, initially, it calculates the ridge ends and ridge bifurcations of each fingerprint image. And then, it estimates the minutiae points for the intersection of each ridge end and ridge bifurcation. In the experimental evaluation, we tested the extracted features of our proposed model using a support vector machine (SVM) classifier and experimental results show that the proposed method can accurately classify different fingerprint images.
  • 关键词:Image processing and Machine Learning;feature extraction; fingerprint images; minutiae points; support vector machine
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