Abstract
Standard histograms, because of their efficiency and insensitivity to small changes, are widely used for content based image retrieval. But the main disadvantage of histograms is that many images of different appearances can have similar histograms because histograms provide coarse characterization of an image. Color histograms too are widely used and suffer from the same problem. In this paper, the technique defined is based on Histogram Refinement [1] and we call it Color and Egde Refinement. Color and Egde Refinement method splits the pixels in a given bucket into several classes just like histogram refinement method. The classes are all related to colors & edges and are based on color & edge coherence vectors.
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Park, T., Chang, M., Park, J. (2005). Color and Edge Refinement Method for Content Based Image Retrieval. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_87
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DOI: https://doi.org/10.1007/11595755_87
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30750-1
Online ISBN: 978-3-540-32284-9
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