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Face detection - mbsahooo - 10-04-2017 Face detection [attachment=17445] Introduction In recent years, face recognition has attracted much attention and its research has rapidly expanded by not only engineers but also neuroscientists, since it has many potential applications in computer vision communication and automatic access control system. Especially, face detection is an important part of face recognition as the first step of automatic face recognition. However, face detection is not straightforward because it has lots of variations of image appearance, such as pose variation (front, non-front), occlusion, image orientation, illuminating condition and facial expression Color Segmentation Detection of skin color in color images is a very popular and useful technique for face detection. Many techniques [12], [13] have reported for locating skin color regions in the input image. While the input color image is typically in the RGB format, these techniques usually use color components in the color space, such as the HSV or YIQ formats. That is because RGB components are subject to the lighting conditions thus the face detection may fail if the lighting condition changes Building Eigenimage Database In order to save time to magnify or shrink an eigenimage to meet the size of the test image, a group of eigenimages was stored in the database so that an appropriate eigenimage can be called with ease without going through image enlarging or shrinking process. The eigenimages were stored in 20 files from 30 pixel-width square image to 220 pixel-width square image with 10-pixel step. The stored eigenimages were normalized by means of dividing the image matrix by its 2nd norm so that the effect of eigenimage size does not affect the face detection algorithm. Test Image Selection After the color-based segmentation process, skin-colored area can be taken apart as shown in Fig. 6. Given this binary image, a set of small test images needs to be selected and passed to the image matching algorithm for the further process. The result of image selection solely based on the color information is shown in Fig. 10. A square box was applied on each segment with the quantified window size which was selected to meet the size of a face. |