Individual Palm Vein Identification: Machine Learning Approach

Abstract

Biometric system has gained more importance in providing high security in individual identification as it uses a network of blood vessels underneath the palm skin. This paper proposes a new algorithm for palm vein identification using a histogram of gradient t(HOG). Raw images of palm hand vein are taken from a public dataset named VP base dataset. Region of interest was extracted after preprocessing stage, after that essential features were extracted by following different steps of the HOG algorithm, which captures edge information inside the images, where they are the vital features containing valuable information. For the purpose of classification Support Vector Machine was used. By experimental work, our algorithm gives promising results than different existing feature descriptors.