Face Detection in Skin-toned Images Using Edge Detection and Feature Extraction Using R and G Channelsthrough Wavelet Approximation

Abstract

Face detection and localization in complex skin toned background is a highly challenging problem. In this paper, use of combination of color spaces and edge detection in red and green channels is proposed for segmenting out the skin-tone regions. Wavelet approximations are used for the extraction of prominent features of face. Experimental results are shown to yield the improved false acceptance rates (FAR) over the algorithms that either use grey scale image for segmentation and the algorithms that do not use any edge detection.

Face Detection in Skin-Toned Images Through Wavelet Edges and Neural Network

“…In [6], there are few false rejections and the number of false acceptance is minimized as the window contents are checked for the presence of face in two different channels (R and G) for matching edge strength. False acceptances are noticed only when approximation images produce similar edges at identical positions.…”

“…PROPOSED ALGORITHM In this paper using the algorithm proposed in [6], input color image is first skin segmented using HSI and YCbCr color spaces. For a detailed survey of color spaces refer [11].…”

“…The use of color space alone sometimes fails to segment the boundary regions of the image. In order to overcome this problem combination of colour spaces for efficient skin segmentation followed by Canny and Prewitt edge detection to demarcate the region boundary is used for input image segmentation [6]. Due to variation in illumination, skin regions may not be properly identified as skin during skin segmentation.…”

“…Researchers are working on adaptive skin color segmentation used for detection [4]. The segmentation using combination of color spaces combined with Canny and Prewitt edge detection for obtaining the region boundaries segment better when compared with the combination of YCbCr color space and Robert Cross edge [5], [6]. There are several challenges while detecting and locating faces in skin toned regions, refer [6].…”

“…The segmentation using combination of color spaces combined with Canny and Prewitt edge detection for obtaining the region boundaries segment better when compared with the combination of YCbCr color space and Robert Cross edge [5], [6]. There are several challenges while detecting and locating faces in skin toned regions, refer [6]. Inspite of using combination of different color spaces during segmentation, it is tedious to demarcate region boundaries between skin and pseudo skin regions and also eliminate these regions from searching process " Fig.…”