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Combined feature descriptor for content based image retrieval

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dc.contributor.author Selvarajah, S
dc.contributor.author Kodithuwakku, S.R
dc.date.accessioned 2014-02-05T19:56:57Z
dc.date.accessioned 2022-06-28T06:46:02Z
dc.date.available 2014-02-05T19:56:57Z
dc.date.available 2022-06-28T06:46:02Z
dc.date.issued 2011-08
dc.identifier.isbn 978-145770035-4
dc.identifier.uri http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/256
dc.description.abstract Content based Image Retrieval (CBIR) allows automatically extracting target images according to objective visual contents of the image itself. Representation of visual features and similarity match are important issues in CBIR. Colour and texture features are important properties in CBIR systems. In this paper, a combined feature descriptor for CBIR is proposed to enhance the retrieval performance for CBIR. This method is developed by exploiting the wavelets and colour histogram moments. First, Haar wavelet is used to decompose colour images into wavelet coefficients. Then image feature extraction and similarity matching are performed by means of histogram moments. Ten categories of colour images are used to test the proposed technique. Experiment results show significant improvement of retrieval efficiency as compared to that of histogram moments as well as 2D Discrete Wavelet Transform. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject 2D Discrete Wavelet Transform en_US
dc.subject colour histogram moments en_US
dc.subject Content based Image Retrieval en_US
dc.subject Haar wavelet en_US
dc.title Combined feature descriptor for content based image retrieval en_US
dc.type Article en_US


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