A hybrid compression technique for segmented hand veins using quad tree decomposition

Abstract

Biometrics are techniques for automatically identifying and authenticating an individual based on his physiological or behavioral characteristics. Hand vein is one of the biometric modalities. Hand vein check measures the shape and size of veins in the back of the hand in a grayscale image. In this paper, hybrid compression technique is applied on ninety hand vein images. This hybrid technique is combining the advantages of lossless techniques and lossy techniques. Only the essential information is selected and compressed using lossless technique, and nonessential information is compressed using lossy technique. The observed parameters are compression ratio (CR), total compression time (TCT), mean square error (MSE), and peak signal to noise ratio (PSNR). The goal is to maximize the CR while preserving images' information. This is acheived using object segmentation procedure and quad tree decomposition (QTD) as preprocessing steps for the compression process. Applying the hybrid technique on the dataset images results in a CR in the range of 89.56%.