Content Based Image Retrieval: A Review Paper?

Content-based image retrieval (CBIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. The term "content" in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. CBIR has been used to describe the process of retrieving desired images from a large collection on the basis of syntactical image features. CBIR is desirable because most web-based image search engines rely purely on metadata and this produces a lot of garbage in the results. Also having humans manually enter keywords for images in a large database can be inefficient, expensive and may not capture every keyword that describes the image. This paper describes a system that can filter images based on their content and provide better indexing and return more accurate results.