Abstract:

In this paper we discuss and an implemented different method of face recognition namely Principal Component Analysis, Discrete Wavelet Transform Cascaded with Principal Component Analysis, Contour Matching and Isodensity Line Maps Cascaded with Hopfield Neural Network. All these algorithms are tested on ORL Database and/or BioID Database. The feasibility of these algorithms for human face identification is presented through experimental investigation. We were able to design these prototype systems, which provides user authentication via facial features. These proposed systems of face recognition may be applied in identification systems, document control and access control.

Keywords:  Face and gesture recognition, image processing and computer vision, pattern analysis, pattern recognition

(Full Paper 698 KB)

Biographies:

	S.T.Gandhe is Assistant Professor in Electronics Engg Department, S. P. College of Engineering, Mumbai, India. He is a member of IEEE. His area of interest includes Image Processing, Pattern recognition and Robotics. He has published ten papers in National Conferences and four papers in International conference. star_stg@yahoo.com
	K.T.Talele is Assistant Professor in Electronics Engg Dept, S. P. College of Engineering, Mumbai., India He is a member of IEEE. His area of interest includes DSP, Image Processing and Multimedia Comm. He has published twenty five papers in National Conferences and four papers in International conference. kttalele@yahoo.co.uk
	A.G.Keskar is Professor in Electronics Engg. Dept and Dean R & D, Visvesvaraya National Institute of Technology, Nagpur. He is a senior member of IEEE. He has published 10 Journal papers and published 15 papers in International Conferences. His area of interest includes Fuzzy logic, Embedded System and Machine Vision. avinashkeskar@yahoo.com

BibTex:

@ARTICLE{P1150729005,

AUTHOR = {S.T.Gandhe and K.T.Talele and A.G.Keskar},

TITLE = {Intelligent Face Recognition Techniques: A Comparative Study},

JOURNAL ={ICGST International Journal on Graphics, Vision and Image Processing, GVIP},

YEAR = {2007},

VOLUME = {07},

ISSUE ={3},

PAGES={53--60}

}

(Full Paper 698 KB)