In this paper, we propose a novel robust line orientation code for palmprint verification, whose performance is improved by using three strategies. Firstly, a modified finite Radon transform (MFRAT) is proposed, which can extract the orientation feature of palmprint more accurately and solve the problem of sub-sampling better. Secondly, we construct an enlarged training set to solve the problem of large rotations caused by imperfect preprocessing. Finally, a matching algorithm based on pixel-to-area comparison has been designed, which has better fault tolerant ability. The experimental results of verification on Hong Kong Polytechnic University Palmprint Database show that the proposed approach has higher recognition rate and faster processing speed.
- Modified finite Radon transform
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence