Abstract A vein recognition algorithm based on fusing all local directional features which are extracted from divided blocks is proposed. Firstly, the acquired binary image is thinned by improved thinning algorithm after vein image preprocessing and the vein skeleton information is obtained. Secondly, the thinned vein image is divided into blocks. Then, every subimage is processed by ridgelet transforming, the dimensions of ridgelet transforming coefficients are reduced by applying principal component analysis, and the eigenvectors of vein image are acquired. Finally, vein images are classified and matched through making use of support vector machine based on the eigenvectors of image. Experimental results show that eigenvectors which are acquired through proposed algorithm have better discrimination, recognition results are affected less by errors that are generated in image acquiring and preprocessing, and the correct recognition rate exceeds 97%.
JIA Xu,XUE Ding-Yu,CUI Jian-Jiang等. Dorsal Hand Vein Recognition Algorithm Based on Ridgelet Transforming of Divided Blocks[J]. , 2011, 24(3): 346-352.
2011, Vol. 24 
