Design of Face Recognition Based on Clustering for Student Present Recording System
碩士 === 國立虎尾科技大學 === 資訊管理研究所 === 99 === The thesis proposes a face recognition technique based on clustering technology. It first adopts the histogram-equalization scheme to solve the high brightness problem. That is, a face image may be highly dark or bright. Subsequently, the proposed technique us...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/26js43 |
| Summary: | 碩士 === 國立虎尾科技大學 === 資訊管理研究所 === 99 === The thesis proposes a face recognition technique based on clustering technology. It first adopts the histogram-equalization scheme to solve the high brightness problem. That is, a face image may be highly dark or bright. Subsequently, the proposed technique uses the local-binary-pattern (LBP) method to extract edge features for a face image. These edge features of an image can be formed as a feature vector for the image. It then utilizes the K-affinity propagation (K-AP) scheme to generate a K-AP clustering model for a set of feature vectors of images. Experimental results show that the performance of the proposed technique is better than that of other clustering methods under consideration here. Consequently, the technique can be applied to face-recognition applications.
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