SIFT applied to CBIR

Content-Based Image Retrieval (CBIR) is a challenging task. Common approaches use only low-level features. Notwithstanding, such CBIR solutions fail on capturing some local features representing the details and nuances of scenes. Many techniques in image processing and computer vision can capture these scene semantics. Among them, the Scale Invariant Features Transform~(SIFT) has been widely used in a lot of applications. This approach relies on the choice of several parameters which directly impact its effectiveness when applied to retrieve images. In this paper, we discuss the results obtained in several experiments proposed to evaluate the application of the SIFT in CBIR tasks.