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Review and research on "semantic gap" problem in the content based image retrieval

Guohua Geng

Open publisher page 4 citations

Abstract

Aim To discuss the gap problem which exists in the CBIR.Methods The form and origin of the problem are explored;from the point of acquiring the image semantics,the methods and their current lacks on solving the problem are studied and analyzed,and towards them some resolving strategies are presented elementarily.Results At present the applying multilayer relevance feedback methods in the CBIR could build and modify the association low-level feature and high-level semantic,which would be helpful to narrow the gap in image retrieval and reach the purpose of semantic retrieval at some extent.Conclusion To achieve the real semantic-based image retrieval would be the most effective approach to settle the problem.

About this research paper

What this paper is about

Aim To discuss the gap problem which exists in the CBIR.Methods The form and origin of the problem are explored;from the point of acquiring the image semantics,the methods and their current lacks on solving the problem are studied and analyzed,and towards them some resolving strategies are presented elementarily.Results At present the applying multilayer relevance feedback methods in the CBIR could build and modify the association low-level feature and high-level semantic,which would be helpful to narrow the gap in image retrieval and reach the purpose of semantic retrieval at some extent.Conclusion To achieve the real semantic-based image retrieval would be the most effective approach to settle the problem.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Aim To discuss the gap problem which exists in the CBIR.Methods The form and origin of the problem are explored;from the point of acquiring the image semantics,the methods and their current lacks on solving the problem are studied and analyzed,and towards them some resolving strategies are presented elementarily.Results At present the applying multilayer relevance feedback methods in the CBIR could build and modify the association low-level feature and high-level semantic,which would be helpful to narrow the gap in image retrieval and reach the purpose of semantic retrieval at some extent.Conclusion To achieve the real semantic-based image retrieval would be the most effective approach to settle the problem.

Key concepts: Semantic gap, Image retrieval, Semantics (computer science), Computer science, Information retrieval, Content-based image retrieval, Feature (linguistics), Relevance (law)

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