For 128-dimensional SIFT feature vectors, using distance matching and cosine similarity measure combining matching method using feature points consistent direction to further reduce false match rate. The experimental results showed that: improved algorithm for image scaling, rotation, light, noise, and small-scale perspective transformation have better matching results. Compared with the original algorithm, while ensuring match points and matching time, based on the improved algorithm for rotation, scaling, noise, blur and light transform the average rate mismatch is reduced by 10 to 20 , for small-scale perspective transformation, mismatch average rate reduction of 5 .

基于SIFT算子的图像匹配算法研究_白廷柱.caj

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