Performance Analysis for Detection and Location of Human Faces in Digital Image With Different Color Spaces for Different Image Formats
Автор: Satyendra Nath Mandal, Kumarjit Banerjee
Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp
Статья в выпуске: 7 vol.4, 2012 года.
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A human eye can detect a face in an image whether it is in a digital image or also in some video. The same thing is highly challenging for a machine. There are lots of algorithms available to detect human face. In this paper, a technique has been made to detect and locate the position of human faces in digital images. This approach has two steps. First, training the artificial neural network using Levenberg–Marquardt training algorithm and then the proposed algorithm has been used to detect and locate the position of the human faces from digital image. The proposed algorithm has been implemented for six color spaces which are RGB, YES, YUV, YCbCr, YIQ and CMY for each of the image formats bmp, jpeg, gif, tiff and png. For each color space training has been made for the image formats bmp, jpeg, gif, tiff and png. Finally, one color space and particular image format has been selected for face detection and location in digital image based on the performance and accuracy.
Face Detection, Artificial Neural Networks, Levenberg–Marquardt Training Algorithm, Color Space, Image Format
Короткий адрес: https://sciup.org/15012337
IDR: 15012337
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