吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 840-846.doi: 10.13229/j.cnki.jdxbgxb201403042

• Orignal Article • Previous Articles     Next Articles

Novel feature set for fingerprint image quality assessment

YUAN Bao-xi1,2,3,SU Fei1,3,ZHAO Zhi-Cheng1,3,CAI An-ni1,3   

  1. 1.School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2.The Chinese People′s Liberation Army 95949 Troops, Cangzhou 061736 China;
    3.Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing 100876,China
  • Received:2012-12-05 Online:2014-03-01 Published:2014-03-01

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Abstract: Based on the mechanism of human visual attention, five features are chosen to simulate the process of subjective quality assessment of fingerprint images. Among these features, two of them are extracted by two proposed methods, a minutiae reliability assessment based on Polar Coordinates Centrum Sensitivity (PCCS) and a gray-scale image contrast based on Otsu algorithm. Experimental results show that this feature set on both Error Back Propagation (BP) Neural Network and Support Vector Machine (SVM) gives high classification accuracy.

Key words: information processing technology, fingerprint image quality assessment, mechanism of visual attention, minutiae reliability assessment, gray scale image contrast assessment

CLC Number: 

  • TN911.73
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