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Conference Paper: Image indexing using weighted color co-occurrence matrix and feature selection

TitleImage indexing using weighted color co-occurrence matrix and feature selection
Authors
Issue Date2007
Citation
Ieee Region 10 Annual International Conference, Proceedings/Tencon, 2007 How to Cite?
AbstractIn this paper, image indexing based on Weighted Color Co-occurrence Matrix (WCCM) feature and Isolation Parameter-based feature selection is introduced. In this method, Isolation Parameter (IP) is used to indicate the visual perception complexity and conduct feature selection for each query image. When indexing images from database in the reduced feature space, the similarities of diagonal elements and non-diagonal elements of CCM feature are weighted separately with different values based on the Isolation Parameters of query image and images from database. The experiments show that the proposed method provides better results than Modified Color Co-occurrence Matrix (MCCM) based method and Sub-range Cumulative Histogram (SCH) based method. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/98942
References

 

DC FieldValueLanguage
dc.contributor.authorLiang, Den_HK
dc.contributor.authorLam, EYen_HK
dc.date.accessioned2010-09-25T18:09:00Z-
dc.date.available2010-09-25T18:09:00Z-
dc.date.issued2007en_HK
dc.identifier.citationIeee Region 10 Annual International Conference, Proceedings/Tencon, 2007en_HK
dc.identifier.urihttp://hdl.handle.net/10722/98942-
dc.description.abstractIn this paper, image indexing based on Weighted Color Co-occurrence Matrix (WCCM) feature and Isolation Parameter-based feature selection is introduced. In this method, Isolation Parameter (IP) is used to indicate the visual perception complexity and conduct feature selection for each query image. When indexing images from database in the reduced feature space, the similarities of diagonal elements and non-diagonal elements of CCM feature are weighted separately with different values based on the Isolation Parameters of query image and images from database. The experiments show that the proposed method provides better results than Modified Color Co-occurrence Matrix (MCCM) based method and Sub-range Cumulative Histogram (SCH) based method. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofIEEE Region 10 Annual International Conference, Proceedings/TENCONen_HK
dc.titleImage indexing using weighted color co-occurrence matrix and feature selectionen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLam, EY:elam@eee.hku.hken_HK
dc.identifier.authorityLam, EY=rp00131en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TENCON.2006.343708en_HK
dc.identifier.scopuseid_2-s2.0-34547572205en_HK
dc.identifier.hkuros125269en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34547572205&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.scopusauthoridLiang, D=26643210600en_HK
dc.identifier.scopusauthoridLam, EY=7102890004en_HK

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