Shivakumar, S.Goel, N.Ananthanarayana, V.S.Cyriac, C.Rajaram, P.2026-02-0620132013 IEEE 2nd International Conference on Image Information Processing, IEEE ICIIP 2013, 2013, Vol., , p. 276-281https://doi.org/10.1109/ICIIP.2013.6707598https://idr.nitk.ac.in/handle/123456789/32681Semantic-based image retrieval has recently become popular as an avenue to improve retrieval accuracy. The 'semantic gap' between the visual features and the high-level semantic features could be narrowed down by utilizing this kind of retrieval method. However, most of the current methods of semantic-based image retrieval utilize visual semantic features and do not consider spatial relationships. We build a system for content-based image retrieval from image collections on the web and tackle the challenges of distinguishing between images that contain similar objects, in order to capture the semantic meaning of a search query. In order to do so, we utilize a combination of segmentation into objects as well as the relationships of these objects with each other. © 2013 IEEE.image segmentationScale Invariant Feature Transform (SIFT)semantic gapSemantic image retrieval