The main goal of this paper is to authenticate people according to their finger textures. We propose to extract Finger Texture (FT) features of the four finger images (index, middle, ring and little) from a low resolution contactless hand image. Furthermore, we apply a new Image Feature Enhancement (IFE) method to enhance the FTs. The resulting feature image is segmented and a Probabilistic Neural Network (PNN) is employed as an intelligent classifier for recognition. Experimental results illustrate that the proposed approach has superior performance than recent published work. Moreover, the best IFE results were obtained with the Equal Error Rate (EER) equal to 4.07%.
|Publication status||Published - 17 Nov 2016|
|Event||2nd IET International Conference on Intelligent Signal Processing 2015, ISP 2015 - London, United Kingdom|
Duration: 1 Dec 2015 → 2 Dec 2015
|Conference||2nd IET International Conference on Intelligent Signal Processing 2015, ISP 2015|
|Period||1/12/15 → 2/12/15|