• Dr.P.Ithaya Rani
• Mrs. K.Dhana Lakshmi

Machine analysis for detection of the human face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and the scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Normalized Gabor Features. For each frame, normalization technique is formulated. The frame is divided into overlapping blocks. Gabor features are extracted in each block by using Gabor filter with selected scale and orientations. TheseGabor filter features are skewed and then passed toAdaBoost classifier with the exemplar of face and non-face signature of the images for detecting thehuman face.The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.

Gabor wavelet, Normalization,Skewness, Ensemble classifier, Human – computer interaction

"AUTOMATIC DETECTION OF HUMAN FACE BY USING NORMALIZED GABOR FILTERS IN VIDEO SEQUENCES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.100-107, September-2018, Available :http://www.jetir.org/papers/JETIRA006337.pdf

"AUTOMATIC DETECTION OF HUMAN FACE BY USING NORMALIZED GABOR FILTERS IN VIDEO SEQUENCES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp100-107, September-2018, Available at : http://www.jetir.org/papers/JETIRA006337.pdf