Performance Comparison Between SURF and SIFT for Content-Based Image Retrieval

摘要

Speeded-Up Robust Feature (SURF) and Scale Invariant Feature Transform (SIFT) have been two well-known methods used in extracting features. This paper presents and analyzes performance comparison between the SURF approach and the SIFT technique for content-based image retrieval (CBIR) application. In particular, we are interested in comparing the accuracy and the response time between these two methods. For the testing purposes, we make use sample images obtained for the Pennsylvania State College of Information Science and Technology database. As it turns out, in this paper, we will demonstrate that in terms of accuracy and speed, SURF shows superior performance compared to SIFT.