| Summary: | 碩士 === 淡江大學 === 電機工程學系碩士在職專班 === 97 === In this paper, we proposed a face recognition based presentation checking system with a robust human face detector. Utilize this detector which can not only extract several human faces information at the same time but the corrected and made a reservation. In the recognition, we use the Region covariance matrices to implement the human face recognition and identity verification.
In this system, we used Region covariance matrices (RCMs) to process human face recognition, because of avoiding the failure of recognition while the input image data is defected. We derive main characteristics of face images by Gabor Filter after dividing the original image as 6 regions, such as facial features (eye, ear, nose, lips and eyebrow). And this method apparently boost, the recognition rate and make our system much more robust. After processing Region covariance matrices, opposite angles of matrix save and present the variation of characteristics between the non- opposite angle. The total variation between the sample image and test image estimate the matrix find out the generalized eigenvalues firstly. Secondly, we find out a identification which is similar as the one from database by searching the minimum distance. Between input images and database. Finally we can find out the input datum’s identifications by gathering the proper samples similar with input datum which are in the bead of the queue.
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