Open AccessHand vein recognition using local block pattern
Author(s) -
Meng Zhaohui,
Gu Xiaodong
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.3353
Subject(s) - block (permutation group theory) , pattern recognition (psychology) , artificial intelligence , computer science , computer vision , mathematics , geometry
A vein recognition method using the local block pattern is presented. After the phase information of a vein image is extracted by a group of Gabor filters and local XOR pattern operators, the phase coding image is divided into some even non‐overlap blocks. These local block patterns can alleviate the effect of noises and enhance the discriminative power. Each block is divided further into some sub‐blocks, and Fisher's linear discriminant is applied here to reduce the dimensionality of the proposed descriptor and improve the performance at the same time. Finally, these histograms of blocks are concatenated to form the descriptor of the whole vein image. The proposed method is evaluated on the hand vein image database and the HK PolyU's database. The results show that the local block pattern strategy plays a crucial role in the vein recognition method. When the sizes of the block and the sub‐block are right, the method can achieve an error equation rate of 0.88 and 0.13% on the two databases, respectively.