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Improved Face Recognition Approach Using Gabor Wavelet and Adaboost Algorithm

机译:Gabor小波和Adaboost算法的改进人脸识别方法

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A new approach is proposed to improve face recognition in the paper. The accurate face is detected by the position relation of the face and the eyes. The face features are extracted using the Gabor wavelet and the adaboost algorithm is used to detect the face and the eyes. In the actual detection of the face, the face is probably inclining, and then we correct the detected face according to the positions of two eyes. The difference size surround function in the Retinex theory is used against illumination to improve the robustness of face recognition. The similarity of the faces is detected by the cosine and distance of face feature vectors. To improve the recognition speed and accurate, a new match algorithm based on Euclidean distance and the vector cosine is proposed. The recognition results are good performed by the experiments.
机译:本文提出了一种新的方法来改善人脸识别能力。通过面部和眼睛的位置关系来检测正确的面部。使用Gabor小波提取人脸特征,并使用adaboost算法检测人脸和眼睛。在人脸的实际检测中,人脸可能是倾斜的,然后根据两只眼睛的位置对检测到的人脸进行校正。 Retinex理论中的差异大小环绕功能可用于照明,以提高人脸识别的鲁棒性。通过脸部特征向量的余弦和距离来检测脸部的相似性。为了提高识别速度和准确性,提出了一种基于欧氏距离和向量余弦的匹配算法。实验结果表明识别效果良好。

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