Improving Content Based Image Retrieval Using Scale Invariant Feature Transform

Provided by: International Journal of Engineering and Advanced Technology (IJEAT)
Topic: Software
Format: PDF
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, the authors attempt to evaluate the application of the SIFT to refine CBIR.

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