Automated thermal face recognition based on minutiae extraction Online publication date: Tue, 23-Jul-2013
by Ayan Seal; Suranjan Ganguly; Debotosh Bhattacharjee; Mita Nasipuri; Dipak Kr. Basu
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 2, No. 2, 2013
Abstract: In this paper, an efficient approach for human face recognition based on the use of minutiae points in thermal face image is proposed. The thermogram of human face is captured by thermal infra-red camera. Image processing methods are used to pre-process the captured thermogram, from which different physiological features based on blood perfusion data are extracted. Blood perfusion data are related to distribution of blood vessels under the face skin. In the present work, three different methods have been used to get the blood perfusion image, namely bit-plane slicing and medial axis transform, morphological erosion and medial axis transform, sobel edge operators. A five layer feed-forward back propagation neural network is used as the classification tool. It has been found that the first method supercedes the other two producing an accuracy of 97.62% with block size 16×16 for bit-plane 4.
Online publication date: Tue, 23-Jul-2013
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Intelligence Studies (IJCISTUDIES):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.If you still need assistance, please email email@example.com