New Approach for Face Recognition across Variable Illuminations
Khushboo B. Trivedi1, V. T. Gaikwad2
1Ms. Khushboo B. Trivedi, ME Final year Appearing, Department of Information Technology, Sipna College of Engineering and Technology, Amravati, India.
2Prof. V.T.Gaikwad, Associate Professor, Department of Information Technology, Sipna College of Engineering and Technology, Amravati, India.
Manuscript received on March 11, 2013. | Revised Manuscript Received on March 12, 2013. | Manuscript published on March 25, 2013. | PP: 45-47 | Volume-1, Issue-6, April 2013. | Retrieval Number: F0247041613/2013©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, a face recognition method based on simultaneous sparse approximations under varying illumination is used. This method consists of two main stages. In the first stage, a dictionary is learned for each face class based on given training examples which minimizes the representation error with a sparseness constraint. In the second stage, a novel image is projected onto the span of the atoms in each learned dictionary. The resulting residual vectors are then used for classification. Furthermore to handle variations in lighting conditions an image relighting technique based on a non-stationary stochastic filter is used to generate multiple frontal images of the same person with variable lighting. As a result, given algorithm has the ability to recognize human faces with good accuracy even when only a single or a very few images are provided for training.
Keywords: Albedo, relighting, simultaneous sparse signal representation.