A new strategy for bridging the semantic gap in image retrieval. (2017)

• Record Type: Journal Article
• Authors: Alzubaidi, Mohammad A.
• Is Part Of: International journal of computational science and engineering. Volume 14:Number 1(2017)
• Page Start: 27
• Page End: 43
• Publication Date: 2017
• Subjects: image indexing -- image retrieval -- semantic gap -- semantic basis functions -- SBFs -- affective basis functions -- ABFs -- basic research -- applied research -- content-based image retrieval -- CBIR -- semantics; Computer science -- Mathematics -- Periodicals; Computer simulation -- Mathematical aspects -- Periodicals; Computational intelligence -- Periodicals; 004.015105
• Languages: English
• ISSNs: 1742-7185

Abstract

Content-based image retrieval (CBIR) research is currently faced with the so called the 'semantic gap' problem. CBIR researchers work at the near end of the gap, applying computer science methods to bridge the gap. Cognitive psychology researchers work at the far end of the gap, studying how humans perceive things in their environment. This article looks at the literature from a new perspective, and presents a structured analysis of what CBIR researchers have done, in their efforts to bridge the gap. This analysis suggests that more emphasis should be placed on studying the far end of the gap. The second part of this article discusses a study conducted at the far end of the gap, to begin the process of developing and testing techniques for externalising and analysing the visual concepts that are evoked by images. This more disciplined approach has the potential to guide researchers in their efforts to bridge the gap.