Sharma - Research Scholar, School of Engineering, Computer Science and Engineering, GD Goenka University, Gurgaon, India
Agrawal - Assistant Professor, School of Engineering, Computer Science and Engineering, GD Goenka University, Gurgaon, India
Munjal - Assistant Professor, School of Engineering, Computer Science and Engineering, G B Pant New Delhi, India.

The most important aspects of image processing are image enhancement. The visual form of an image can be enhanced by using image enhancement techniques for better human interpretation. In this research paper we discuss an   outline and analysis of commonly used image enhancement techniques using finger vein image or personal authentication. Also, experiments are carried out to compare performance of various types of filters for removal of noise from the noisy images through evaluation performance parameter such as mean square error (MSE), peak signal to noise ratio (PSNR) values and structural similarity (SSIM). It was found that application of max filter technique ensures an improved quality of the finger vein image. The mean filter is most advanced in de-noising the images. Mean filter is most efficient in eliminating the salt and pepper noise. From the experiments performed on finger vein image using SDUMLA-HMT database, it is proven that Weiner filters are outstanding for elimination of Gaussian Speckle and Poisson noises and thus, Weiner filter is found to be most appropriate and well-suited for eliminating nearly all types of noise.

Finger Vein, Filters, Histogram Equalization, Image Enhancement, MSE, Noise, PSNR, SSIM