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The Study of Entrance Guard & Check on Work Attendance System Based on Face Recognition

In this paper, the core algorithm is studied, which aiming at developing a robust and practical entrance guard & check on work attendance system based on face recognition, and this system is applied to the logistics management industry. Firstly, this algorithm divides the image into block images, which are also called sub-images. Then the well-known Fisher method is directly employed to the selecting sub-images obtained from the previous step, and the new lower dimensionality patterns that replace the original patterns are obtained. Finally the recognition results are obtained by the general minimum distance classifier. The ORLface image database is made use of to simulate and the results shows that this method presented in this paper is obviously superior to the traditional Fisher method. And when the training sample is only one, the recognition rate of 90.83 percent is achieved. It is indicate that M-FLDA can not only accelerate recognition speed by reducing dimensionality but also reduce the memory capacity. Finally, the preliminary study of solving facial pose changes is presented.