Aiming at the problem that SIFT algorithm is highly complex, has poor real-time performance, and is not practical in high-dimensional image registration, a SIFT algorithm (SIFT-LDA) based on linear discriminant analysis (LDA) is proposed. First, the feature point vector of the image is extracted using SIFT algorithm, and then the LDA method is used to extract features and reduce the dimension. Experiments are conducted on high-dimensional natural images and single face images. The experimental results show that SIFT-LDA algorithm has better real-time performance than traditional SIFT algorithm while ensuring matching accuracy, and its matching time is shortened by nearly half compared with traditional SIFT algorithm.
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