Fingerprint image segmentation based on linear classifier

Chunxiao Ren; Yilong Yin; Jun Ma

doi:10.1117/12.774816

14 November 2007 Fingerprint image segmentation based on linear classifier

Chunxiao Ren, Yilong Yin, Jun Ma

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67905J (2007) https://doi.org/10.1117/12.774816
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Fingerprint segmentation is an important step in automatic fingerprint identification fields. This paper discusses a new method, which is based on a linear classifier, to enhance the performance of fingerprint image segmentation. The novel linear classifier is a label box that is employed to establish a model and deal with fingerprint image quickly and accurately. In order to evaluate the performance of the new method in comparison to the methods based on other linear and nonlinear classifiers, experiments are performed on FVC2000 DB2. The experimental results show the proposed method is able to provide more accurate high-resolution segmentation results than those of previously known ones because only 0.80% of the pixels are misclassified by the method, while the nonlinear classifier, quadric surface classifier, misclassifies 0.97% of the pixels.

Citation Download Citation

Chunxiao Ren, Yilong Yin, and Jun Ma "Fingerprint image segmentation based on linear classifier", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67905J (14 November 2007); https://doi.org/10.1117/12.774816

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