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Face recognition algorithm based on wavelet transform and local linear embedding
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DOI：10.1007/s10586-018-2157-4.png)
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Abstract
En 中文
In this paper, a face recognition fusion algorithm, namely WT-LLE-LSSVM, based on wavelet transform (WT) and local linear embedding (LLE) is proposed. Firstly, the face image is pre-processed, and decomposed by Wavelet Transform to obtain four components of face image; then, the LLE algorithm is carried out to extract the features from the four components respectively, and the weighted fusion is used to obtain the face recognition feature vector; Finally, least squares support vector machine (LSSVM) is conducted to learn the training samples with feature vector reduction, and the classifier of face recognition is established. In the case of different pixels, three face databases are chosen to test some main performance indexes such as recognition rate, speed and time of the algorithm. The simulation results show that compared with the traditional face recognition algorithm, the proposed algorithm can improve the face recognition rate, as well as the computing rate, and enhance the efficiency of face recognition.
Keywords:
Face recognition
Wavelet transform
Locally linear embedding
Least squares support vector machine
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