Enhancement of Vein Patterns in Hand Image for Biometric and Biomedical Application using Various Image Enhancement Techniques

Abstract

Captured hand image needs better enhancement technique to detect the vein patterns, due to existence of indistinct state and unwanted noise in hand image which result in false detection of veins. The image preprocessing such as image enhancement techniques are necessary to improve the image for visual perception of humans and making further easy processing steps on the resultant images by machines. This paper explains various enhancement techniques such as image negative, gray level slicing, histogram equalization, contrast stretching, laplacian sharpening, unsharp masking, high boost filtering, and histogram equalization of high boost filter. These techniques are applied on the hand image using (OpenCV) open source computer vision library developed by Intel. A comparative study of all these enhancement techniques is carried out to find the best technique to enhance hand vein pattern. The result shows the histogram equalization of high boost filtering technique provides better enhancement of vein pattern. Image quality measures (IQMs) are figures of merit used for the evaluation of imaging systems are also evaluated.