Face Recognition with Single Sample per Class Using Cs-lbp and Gabor Filter
نویسنده
چکیده
In face recognition Local appearance based methods has achieved greater performance. In this paper, we have proposed single sample per class using Center Symmetric Local Binary Pattern and Gabor Filter. Gabor Filter extracts the textual feature and generates a binary face templat and the binary face template acts like a mask to extract local texture information using Center Symmetric Local Binary Pattern. Face features which are evaluated from CS-LBP has better performance.
منابع مشابه
An Efficient Face Recognition Using Dct, Adaptive Lbp and Gabor Filter with Single Sample per Class
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