• Mohit Admane
• Prof. Hirendra Hajare

Face detection from a digital image or video stream is used often for various purposes. But sometimes a system detects an object or area as a face where there is no face at all. This paper presents a technique to reduce such wrong detection rate introducing human skin color (HSC) characteristic. The general property of human skin in RGB color space is that it possesses R>G>B (i.e., red values are higher than green value and green value is higher than blue). In this study, such HSC property has been incorporated with the popular Haar Feature Based Face Detection (HFFD) in OpenCV, to reduce wrong detection of faces. Proposed HFFD with HSC (HFFD-HSC) has been tested and compared with standard HFFD rigorously on large number images with single and multiple faces. Experimental results identified the effectiveness of HSC incorporation in HFFD to improve its performance reducing wrong detection of faces.

Haar feature based face detection; OpenCV; skin color analysis; RGB;

"IMPROVEMENT OF HAAR FEATURE BASED FACE DETECTION IN OPENCV INCORPORATING HUMAN SKIN COLOR", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 1, page no.85-88, January-2021, Available :http://www.jetir.org/papers/JETIREK06021.pdf

"IMPROVEMENT OF HAAR FEATURE BASED FACE DETECTION IN OPENCV INCORPORATING HUMAN SKIN COLOR", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 1, page no. pp85-88, January-2021, Available at : http://www.jetir.org/papers/JETIREK06021.pdf