A face recognition system based on the Radon transform

• Main Authors: Kun-Wei Lai, 賴昆煒
• Other Authors: 作者未提供
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/72169994749382168137

碩士 === 銘傳大學 === 電腦與通訊工程學系碩士班 === 100 === In recent years, the bio-authentication technology such as the face recognition, iris recognition, fingerprint recognition, palm print recognition and voice recognition becomes popular. Among the face recognition is the most widely be used, because user don''t need to wear other devices and don''t need to contact with these devices. We can take the all information needed for face recognition only by use the simple camera, Therefore, the face recognition could be the most convenient recognition of the bio-authentication technology. We proposed the real-time face recognition system based on the Radon transform. In the face detection, we use the eyes detection result of the OpenCV to find the where is the face and what size of the face. And then we use the Radon Transform to decide the human face is front face or not. In the face recognition, we use the PCA to reduce the data dimension and then we use the LDA to improve the discrimination of feature vectors to increase difference between different class feature vectors. Finally, we take this image of feature vectors to use the cosθ compare with the database. If the value of the greatest of the cosθ, it means this image is the human in the database. In the experiment section, our face database is created by ourselves to perform all the simulations. The face database is contains 15 individuals, 300 images from four different light sources and five different perspective. We use 10 individuals (different image number) as training patterns, other images as testing patterns, the results show the best recognition rate can achieve 100%。The images of other 5 individuals (100 images) are used as invader test images, the best recognition result can achieve 98% true positive rate and 100% false negative rate. The experiment results showed that we proposed the face recognition system based on the Radon transform can achieve good recognition results.