A fast color feature for real-time image retrieval

In this paper, a fast color feature is presented for real-time image retrieval. The feature is based on Dense SIFT (DSIFT) in the multi-scale RGB space. A new sum function is proposed to accelerate feature extraction instead of Gaussian weighting function. In addition, a novel randomized segment-based sampling algorithm is introduced to filter out superfluous features. In the image retrieval stage, a similarity metric is provided to measure the match between the query and reference images. After the experiments are conducted, RGB-DSIFT is more resistant to common image deformations than the original DSIFT, and more efficient than SIFT, CSIFT, GLOH feature in the processing time.