|
| |||
Face Recognition under Variation of Pose and Illumination using Independent Component Analysis Kailash J. Karande.a Sanjay N.Talbar.b a Department of Information Technology, Sinhgad Institute of Technology, Lonavala, Pune, Maharashtra State, India. b Department of Electronics & Telecommunication, SGGS Institute of Engineering &Technology, Nanded, Maharashtra State, India.This paper addresses the problem of face recognition under variation of illumination and poses with large rotation angles using Independent Component Analysis (ICA). Face recognition using ICA, based on information theory concepts, seek a computational model that best describes face, by extracting most relevant information contained in that face. ICA approach used here to extract global features seems to be an adequate method due to its simplicity, speed and learning capability. The preprocessing is done by Principle Component Analysis (PCA) before applying the ICA algorithm for training of images. The independent components obtained by ICA algorithm are used as feature vectors for classification. The Euclidian distance classifier is used for testing of the images. The variation in illumination and facial poses up to 1800 rotation angle is used by the proposed method and result shows that the recognition improved significantly. Keywords: Face recognition, Independent component analysis (ICA), Principle component analysis (PCA), Pose variance, Illumination variance.
(
BibTex: @ARTICLE{P1150802003, AUTHOR = { Kailash J. Karande and Sanjay N.Talbar }, TITLE = {Face Recognition under Variation of Pose and Illumination using Independent Component Analysis}, JOURNAL ={ICGST International Journal on Graphics, Vision and Image Processing, GVIP}, YEAR = {2008},
VOLUME = {08}, ISSUE ={IV}, PAGES={1--6} }
( | |||
|
|
P1150802003
