| Paper Details: | Downloads: 449 |
| Serial Number: | P1150529101
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| Title: | Image Retrieval based on Invariant Features and Histogram Refinement
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| Authors: | MOHAMED EISA and IBRAHIM ELHENAWY and A.E.ELALFI and HANS BURKHARDT
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| Abstract: | Colour histograms are widely used for content-based image retrieval. Their advantages are efficiency, and insensitivity to small changes in camera viewpoint. However, their drawback is that all structural information is lost. Colour histograms lack spatial information, so images with very different appearances can have similar histograms. In this paper we try to solve the problem of losing the structural information in colour histogram by extending the colour histogram approach by features that take into account the relations within a local pixel neighbourhood [9, 10, 11]. Also, to solve the problem of lack of spatial information, a histogram-based method is used for comparing images that incorporates spatial information which classifies each pixel in a given colour bin as either coherent or incoherent based on whether it is part of large similarly-coloured region. Experimental results show that this technique can give superior results for image retrieval.
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| Keywords: | Image Retrieval, Knowledge Discovery, Data Mining, Colour Histograms, Intelligent Agent
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| Journal/Conference: | ICGST Conference on Graphics, Vision and Image Processing, GVIP-05
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| Volume: | 5
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| Issue: | C1
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| Submission Date: | 5/1/2005 12:00:00 AM
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| Review Date: | 8/1/2005 12:00:00 AM
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| Publishing Date: | 12/19/2005 12:00:00 AM
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| Article Downloads: | 449
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