Vein pattern recognition is one of the latest biometric techniques researched today. The new biometric system based on palm veins acquired by an infrared image offers a high level of accuracy. Oriented features are generally extracted as information for palm vein recognition. However

the use of oriented features is not always effective and computational simple. To simplify the computational complexity and make full use of the palm-vein information

a fast and robust approach by extracting oriented features is proposed in this paper. The images in the PolyU MSpalmprint ROI Database are used as original images. This is followed by the nonlinear enhancement so that the vein patterns from ROI images can be observed more clearly. The background intensity profiles are estimated by dividing the images into 32×32 blocks

and the average gray-levels in each block are computed and resized to the same size as the original image using a bicubic interpolation. Then

the resulting image is subtracted from the original ROI image

besides

CLAHE(Contrast Limited Adaptive Histogram Equalization)is employed to obtain the normalized and enhanced palm-vein image.Small line segments can approximated vessels in palm vein images. The radon transform is an effective tool to identify such line-like palm-vein features. Based on a modified local pattern

the orientation filter

which is derived from Radon transform is improved to extract features. Since the veins appear darker in the palm-vein images

the line direction that results in minimum response is encoded as the dominant direction. Feature matrix composed by the dominant direction is encoded by using 3-bit binary number. With respect to computational complexity

the similarity (also matching scores that range from 0 to 1)between probe images and gallery images is calculated by combining the Hamming distance and global matching methods. As a result

we identify the probe images by setting a threshold for the Matching scores. The modified local pattern proposed in this paper has a better performance in extracting palm-vein texture information. By optimizing the orientation filter

the EER is further improved to 0.0002 % from the images of the PolyU database

which conforms the rotation invariance of the proposed approach. In addition

with the use of encoding and global matching methods

we achieved a speed of 11 ms and 4 ms in feature extracting and matching for each image

respectively. Besides

the proposed method can also achieve good performance under the condition of poor image enhancement. Finally

experimental results show that the proposed approach can improve the speed and the accuracy of the palm-vein recognition system. Radon transform is widely-used in texture analysis. However

when used in palm-vein recognition

it still needs much improvement for better identifying line-like palm-vein features. We propose an improvement for a better use of the Radon transform in oriented features extracting. With respect to the speed of the recognition

encoding and global matching are used in this paper. Compared with other palm-vein recognition methods

the experimental results presented in this paper conform the superiority and robustness of the proposed approach in terms of both computational complexity and the use of palm-vein oriented information.