Multiple palm features extraction method based on vein and palmprint

Abstract

Contactless acquisition enables palm identification device to be more easily accepted by people who worry about hygiene problems. The uncertainty of the position between the palm and the device leads to the horizontal rotation, translation, scaling of palm image. This paper proposes a novel feature extraction method which can reflect the geometric features of palmprint and palm vein without being affected by the scaling, rotation and translation. Firstly, the inscribed circle of palm is obtained, and then several radiation segments are made between the circle center and circumference. The wiring direction from the center to the root points of both middle finger and ring finger is as the direction of the first radiation segment. Secondly, the gradient value of pixels in the inscribed circle is calculated by creating template. The feature vector space is established by the relative radius of radiation segment’s centroids. Finally, the palm image database is established based on the application. The feature stability in different size of sub-template and recognition performance in different number of feature line segments are analyzed. In the size of sub-template is equal to three and the number of feature line segments is 60, the equal error rate is less than 0.4% and feature extraction time is 0.0019 s. The experimental results show that the method can extract out stable characteristics whenever the hand image is scaled, rotated or translated.