A Comparison of the Vein Patterns in Hand Images with other image enhancement techniques

ABSTRACT This research work presents an overview of image enhancement processing techniques in spatial domain and frequency domain to enhance the vein patterns in hand image and a comparative study is made between these techniques. 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 research work explains various enhancement techniques such as image negative, gray level slicing, contrast limited adaptive histogram equalization, Laplacian filtering, unsharp masking, sharpening and high boost filtering. Homomorphic filter characteristic is used for nonlinearities (mainly the logarithm) to transform convolved or nonlinearly related signals to additive signals and then to process them by linear filters. A comparative study on all these enhancement techniques is carried out to find the best technique to enhance hand vein pattern. The various contrast enhancement techniques are effectively applied on the captured hand image. From these techniques, homomorphic filtered image gives the best result and could give exact information about the vein pattern in the captured image. As a result, vein can be detected using this technique appears to be clearer and would provide ease further analysis in vein applications. Image quality measures (IQMs) are also evaluated and tabulated.