用于指纹图像质量评价的新特征集

doi:10.13229/j.cnki.jdxbgxb201403042

Abstract

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

YUAN Bao-xi,SU Fei,ZHAO Zhi-Cheng,CAI An-ni. Novel feature set for fingerprint image quality assessment[J].吉林大学学报(工学版), 2014, 44(3): 840-846.

References

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