@article{(Open Science Index):https://publications.waset.org/pdf/12187,
	  title     = {A New Face Detection Technique using 2D DCT and Self Organizing Feature Map },
	  author    = {Abdallah S. Abdallah and  A. Lynn Abbott and  Mohamad Abou El-Nasr},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper presents a new technique for detection of
human faces within color images. The approach relies on image
segmentation based on skin color, features extracted from the two-dimensional
discrete cosine transform (DCT), and self-organizing
maps (SOM). After candidate skin regions are extracted, feature
vectors are constructed using DCT coefficients computed from those
regions. A supervised SOM training session is used to cluster feature
vectors into groups, and to assign “face" or “non-face" labels to those
clusters. Evaluation was performed using a new image database of
286 images, containing 1027 faces. After training, our detection
technique achieved a detection rate of 77.94% during subsequent
tests, with a false positive rate of 5.14%. To our knowledge, the
proposed technique is the first to combine DCT-based feature
extraction with a SOM for detecting human faces within color
images. It is also one of a few attempts to combine a feature-invariant
approach, such as color-based skin segmentation, together with
appearance-based face detection. The main advantage of the new
technique is its low computational requirements, in terms of both
processing speed and memory utilization.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {3},
	  year      = {2007},
	  pages     = {489 - 493},
	  ee        = {https://publications.waset.org/pdf/12187},
	  url   	= {https://publications.waset.org/vol/3},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 3, 2007},
	}