| Summary: | 碩士 === 國立臺北科技大學 === 資訊工程系研究所 === 102 === In recent years, authentication demand becomes more and more eager. Face recognition has the advantage of natural and contactless than other biometric such as iris, fingerprint, or palm vein, etc. Furthermore, face recognition can identifies multiple users at the same time. But face recognition technology was regarded as the hardest research on biometrics. Because similarity degree of facial features is higher on different people, though it is great for face detection, but it is vexation a for face recognition. In addition, facial features have considerable variation because head pose change, expression change, and environment brightness change.
We think color information also is important element of recognize face besides facial features. And color information does not complexity operating. Hence, this paper uses Active Shape Model extract facial features, we capture color features on cheek besides color on the positions of feature points. Experimental result shows that the proposed method promotes recognition success rate is about 4~5% than original ASM.
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