Image Retrieval Based on Region of Interest

Content Based Image Retrieval (CBIR) is browsing, searching and navigation of images from large image databases based on their visual content. CBIR has been an active area of research for more than a decade. Many CBIR systems have been developed; like QBIC [Flickner et al. (1995)], Simplicity [Wang et al. (2001)], and Blob world [Carson et al.(2002)]. A detailed survey of CBIR techniques can be found in [Lew et al. (2006), Vassilieva (2009), Pradnya and Vikhar (2010)]. Traditional CBIR systems use low level features like color, texture, shape and spatial location of objects to index and retrieve images from databases. Low level features can be global or local (region based). Global feature based CBIR systems [Ciocca et al. (2011), Lin et al. (2009), Wang et al. (2011), Zhiwen et al. (2012)] fail to compare the regions or objects in which a user may be interested. Therefore Region Based Image Retrieval (RBIR) is shown to be more effective in reflecting the user requirement in the literature.