改进 PCA-SIFT 的电子标签图像匹配算法.

In order to solve the problems of long time consuming and matching rate of SIFT algorithm in electronic label image matching, an image matching algorithm based on improved PCA-SIFT is proposed. Firstly, the key feature points of the image are obtained by SIFT algorithm, and the 128D feature vector is formed, then the K-means clustering is carried out after PCA dimension reduction is used to realize the effective identification of electronic tags, and the invalid pictures are initially eliminated. Finally, RANSAC affine transformation is used to realize the fast matching of electronic tags. The experimental results show that compared with other matching algorithms, the improved algorithm can quickly eliminate invalid pictures, improve the matching efficiency, and has a good detection effect in a more complex environment. Meanwhile, the improved SIFT algorithm based on PCA processing saves the processing time by 0.1 s, it can increase the processing speed by more than 2 times compared with the traditional single SIFT algorithm. The matching rate is increased by 6%, and this method has better matching effect. [ABSTRACT FROM AUTHOR]