Title :
Finger Vein Image Denoising Based on Compressive Sensing
Author :
Chen, Meimei ; Guo, Shuxu ; Wang, Yao ; Wu, Bin ; Yu, Siyao ; Shao, Xiangxin ; Wang, Lang
Author_Institution :
Coll. of Electron. Sci. & Eng., Jilin Univ., Changchun, China
Abstract :
To extract venous information from noise-added images acquired by infrared sensor, in this paper, we presents a compressive sensing (CS) based application - gradient projection for sparse reconstruction (GPSR) - to reduce noise in synthetic vein images and real finger vein images respectively. Then compares the result with the reconstruction by wavelet threshold denoising algorithm. The results show that the GPSR has better performance than the wavelet threshold method in reducing noise, avoids losing the edge information of finger vein, and thus provides more accurate information for vein recognition and extraction.
Keywords :
blood vessels; image denoising; image recognition; image reconstruction; infrared detectors; medical image processing; sparse matrices; wavelet transforms; compressive sensing; finger vein image denoising; gradient projection; infrared sensor; noise-added images; sparse reconstruction; vein recognition; venous information; wavelet threshold denoising algorithm; Biomedical imaging; Data mining; Fingers; Frequency; Image coding; Image denoising; Image reconstruction; Noise reduction; Pollution measurement; Veins;
Conference_Titel :
Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4712-1
Electronic_ISBN :
2151-7614
DOI :
10.1109/ICBBE.2010.5517770