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• W2152100107 abstract "The histogram of image intensities is used extensively for recognition and for retrieval of images and video from visual databases. A single image histogram, however, suffers from the inability to encode spatial image variation. An obvious way to extend this feature is to compute the histograms of multiple resolutions of an image to form a multiresolution histogram. The multiresolution histogram shares many desirable properties with the plain histogram, including that they are both fast to compute, space efficient, invariant to rigid motions, and robust to noise. In addition, the multiresolution histogram directly encodes spatial information. We describe a simple yet novel matching algorithm based on the multiresolution histogram that uses the differences between histograms of consecutive image resolutions. We evaluate it against five widely used image features. We show that with our simple feature we achieve or exceed the performance obtained with more complicated features. Further, we show our algorithm to be the most efficient and robust." @default.
• W2152100107 created "2016-06-24" @default.
• W2152100107 creator A5024032759 @default.
• W2152100107 creator A5051975921 @default.
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• W2152100107 date "2004-07-01" @default.
• W2152100107 modified "2023-09-30" @default.
• W2152100107 title "Multiresolution histograms and their use for recognition" @default.
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• W2152100107 doi "https://doi.org/10.1109/tpami.2004.32" @default.
• W2152100107 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18579943" @default.
• W2152100107 hasPublicationYear "2004" @default.
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