@article{(Open Science Index):https://publications.waset.org/pdf/9997450,
	  title     = {Face Recognition Based On Vector Quantization Using Fuzzy Neuro Clustering},
	  author    = {Elizabeth B. Varghese and  M. Wilscy},
	  country	= {},
	  institution	= {},
	  abstract     = {A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {7},
	  number    = {11},
	  year      = {2013},
	  pages     = {1525 - 1534},
	  ee        = {https://publications.waset.org/pdf/9997450},
	  url   	= {https://publications.waset.org/vol/83},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 83, 2013},
	}