Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation

An approach of representing meanings of images based on associative values with lexicons is proposed. For this, the semantic tolerance relation model (STRM) that reflects the tolerance degree between defined lexicons is generated, and two factors of semantic relevance (SR) and visual similarity (VS)...

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Main Author: Ying Dai
Format: Article
Language:English
Published: Wiley 2011-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2011/786427
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author Ying Dai
author_facet Ying Dai
author_sort Ying Dai
collection DOAJ
description An approach of representing meanings of images based on associative values with lexicons is proposed. For this, the semantic tolerance relation model (STRM) that reflects the tolerance degree between defined lexicons is generated, and two factors of semantic relevance (SR) and visual similarity (VS) are involved in generating associative values. Furthermore, the algorithm of calculating associative values using pixel-based bidirectional associative memories (BAMs) in combination with the STRM, which is easy in implementation, is depicted. The experiment results of multilexicons-based retrieval by individuals show the effectiveness and efficiency of our proposed method in finding the expected images and the improvement in retrieving accuracy because of incorporating SR with VS in representing meanings of images.
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institution Kabale University
issn 1687-5680
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language English
publishDate 2011-01-01
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spelling doaj-art-33b21e96a88944fdb2b45344d7499d9d2025-02-03T01:03:42ZengWileyAdvances in Multimedia1687-56801687-56992011-01-01201110.1155/2011/786427786427Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance RelationYing Dai0Faculty of Software and Information Science, Iwate Prefectual University, Sugo 152-52, Iwate, 020-0193 Takizawa, JapanAn approach of representing meanings of images based on associative values with lexicons is proposed. For this, the semantic tolerance relation model (STRM) that reflects the tolerance degree between defined lexicons is generated, and two factors of semantic relevance (SR) and visual similarity (VS) are involved in generating associative values. Furthermore, the algorithm of calculating associative values using pixel-based bidirectional associative memories (BAMs) in combination with the STRM, which is easy in implementation, is depicted. The experiment results of multilexicons-based retrieval by individuals show the effectiveness and efficiency of our proposed method in finding the expected images and the improvement in retrieving accuracy because of incorporating SR with VS in representing meanings of images.http://dx.doi.org/10.1155/2011/786427
spellingShingle Ying Dai
Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation
Advances in Multimedia
title Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation
title_full Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation
title_fullStr Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation
title_full_unstemmed Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation
title_short Representing Images' Meanings by Associative Values with Given Lexicons Considering the Semantic Tolerance Relation
title_sort representing images meanings by associative values with given lexicons considering the semantic tolerance relation
url http://dx.doi.org/10.1155/2011/786427
work_keys_str_mv AT yingdai representingimagesmeaningsbyassociativevalueswithgivenlexiconsconsideringthesemantictolerancerelation