Face detection is considered as a challenging problem in the field of
image analysis and computer vision. There are many researches in this area, but
because of its importance, it needs to be further developed. Successive Mean
Quantization Transform (SMQT) for illumination and sensor insensitive operation
and Sparse Network of Winnow (SNoW) to speed up the original classifier based face
detection technique presented such a good result. In this paper we use the
Mean of Medians of CbCr (MMCbCr) color correction approach to enhance the
combined SMQT features and SNoW classifier face detection technique. The
proposed technique is applied on color images gathered from various sources
such as Internet, and Georgia Database. Experimental results show that the face
detection performance of the proposed method is more effective and accurate
compared to SFSC method.
Cite this paper
M. El-Sayed and N. Ahmed, "Enhanced Face Detection Technique Based on Color Correction Approach and SMQT Features," Journal of Software Engineering and Applications
, Vol. 6 No. 10, 2013, pp. 519-525. doi: 10.4236/jsea.2013.610062
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