Canny Edge Dectection Essay

3013 WordsApr 21, 201313 Pages
International Journal of Computer Theory and Engineering, Vol. 5, No. 1, February 2013 Face Detection in Skin-Toned Images Using Edge Detection and Feature Extraction Using R and G Channels through Wavelet Approximation H. C. VijayLakshmi and S. Patilkulkarni  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. Index Terms—Face detection, localization, edge, wavelet, r and g channel. I. INTRODUCTION Face detection and localization is the task of checking whether the given input image contains any human face, and if so, returning the location of the human face in the image. Face detection is difficult mainly due to a large component of non-rigidity and textural differences among faces. The great challenge for the face detection problem is the large number of factors that govern the problem space [1], [2]. The long list of these factors include the pose, orientation, facial expressions, facial sizes found in the image, luminance conditions, occlusion, structural components, gender, ethnicity of the subject, the scene and complexity of image‟s background. The scene in which the face is placed ranges from a simple uniform background to highly complex backgrounds. In the latter case it is obviously more difficult to detect a face. Faces appear totally different under different lighting conditions. A thorough survey of face detection research work is available in [1],[2]. In terms

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