@article{(Open Science Index):https://publications.waset.org/pdf/5120,
	  title     = {Face Detection using Variance based Haar-Like feature and SVM},
	  author    = {Cuong Nguyen Khac and  Ju H. Park and  Ho-Youl Jung},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper proposes a new approach to perform the
problem of real-time face detection. The proposed method combines
primitive Haar-Like feature and variance value to construct a new
feature, so-called Variance based Haar-Like feature. Face in image
can be represented with a small quantity of features using this
new feature. We used SVM instead of AdaBoost for training and
classification. We made a database containing 5,000 face samples
and 10,000 non-face samples extracted from real images for learning
purposed. The 5,000 face samples contain many images which have
many differences of light conditions. And experiments showed that
face detection system using Variance based Haar-Like feature and
SVM can be much more efficient than face detection system using
primitive Haar-Like feature and AdaBoost. We tested our method on
two Face databases and one Non-Face database. We have obtained
96.17% of correct detection rate on YaleB face database, which is
higher 4.21% than that of using primitive Haar-Like feature and
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {12},
	  year      = {2009},
	  pages     = {2947 - 2950},
	  ee        = {https://publications.waset.org/pdf/5120},
	  url   	= {https://publications.waset.org/vol/36},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 36, 2009},