Image retrieval based on enhanced binary feature
Huang Cha · Computer Engineering and Applications Journal · 2015
In this paper it introduces an algorithm of image retrieval for embedded system, which uses local features to do image retrieval. In order to reduce the time cost and get high precision, it improves SIFT feature and descriptor. It replaces Gauss filter with mean filter in detection of scale-space extrema stage. It projects SIFT feature into binary descriptor with sparse matrix. It searches and matches object with multi-probe LSH based on K-means. By doing a series of experiments scale, rotation, blur, illumination, it can draw a conclusion that the algorithm has better performance than traditional state of arts.