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A Content Based Image Retrieval Model for E-Commerce

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dc.contributor.author Gibson Kimutai
dc.contributor.author Prof. Wilson Cheruiyot
dc.contributor.author Dr. Calvins Otieno
dc.date.accessioned 2025-02-23T08:37:40Z
dc.date.available 2025-02-23T08:37:40Z
dc.date.issued 2018-11
dc.identifier.issn 2319-7242
dc.identifier.uri http://ir.ttu.ac.ke/xmlui/handle/123456789/98
dc.description.abstract In the last decade, large database of images have grown rapidly. This trend is expected to continue in to the future. Retrieval and querying of these image in efficient way is a challenge in order to access the visual content from large database. Content Based Image Retrieval (CBIR) provides the solution for efficient retrieval of image from these huge image database. Many research efforts have been directed to this area with color feature being the mostly used feature because of its ease of extraction. Although many research efforts have been directed to this area, precision of majority of the developed models are still at less than 80%. This is a challenge as it leads to unsatisfying search results. This paper proposes a Content Based Image Retrieval model for E-Commerce. en_US
dc.language.iso en en_US
dc.publisher International journal of Engineering and computer science en_US
dc.subject mage retrieval, text-based image retrieval, content-based image retrieval, E-Commerce, E-Bay, shape, performance evaluation, precision, recall en_US
dc.title A Content Based Image Retrieval Model for E-Commerce en_US
dc.type Article en_US


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