Fingerprint Recognition using Texture Features

Manidipa Saha, Jyotismita Chaki, Ranjan Parekh

Abstract: This paper proposes an efficient scheme of fingerprint recognition for biometric identification of individuals. Three statistical features are extracted from fingerprint images and represented using a mathematical model. These features are (1) an entropy coefficient, computed from the intensity histogram of the image, (2) a correlation coefficient, computed by correlation operation between the original image and a filtered version of the image obtained using a 2D median filter, and (3) an energy coefficient, obtained by first subjecting the image to a 5-level wavelet decomposition and thereafter computing the percentage energy of the approximation coefficient obtained after the 5th level decomposition. The approach is tested over a dataset of 80 images divided into 10 classes and is seen to provide accurate recognition results.

Keywords: Fingerprint recognition, entropy, correlation, wavelet energy

How to Cite?: Manidipa Saha, Jyotismita Chaki, Ranjan Parekh, "Fingerprint Recognition using Texture Features", Volume 2 Issue 12, December 2013, International Journal of Science and Research (IJSR), Pages: 265-270, https://www.ijsr.net/getabstract.php?paperid=02013578, DOI: https://dx.doi.org/10.21275/02013578