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<p><it>Abstract</it>—We present a method to locate an “object” in a color image, or more precisely, to select a set of likely locations for the object. The model is assumed to be of known color distribution, which permits the use color-space processing. A new method is presented, which exploits more information than the previous Backprojection Algorithm of Swain and Ballard at a competitive complexity. Precisely, the new algorithm is based on matching <it>local histograms</it> with the model, instead of directly replacing pixels with a confidence that they belong to the object. We prove that a simple version of this algorithm degenerates into Backprojection in the worst case. In addition, we show how to estimate the scale of the model.</p><p>Results are shown on pictures digitized from the famous “Where is Waldo” books. Issues concerning the optimal choice of a color space and its quantization are carefully considered and studied in this application. We also propose to use <it>co-occurrence histograms</it> to deal with cases where important color variations can be expected.</p>
Object recognition, focus of attention, color images, color quantization, color histograms.
Gérard Medioni, François Ennesser, "Finding Waldo, or Focus of Attention Using Local Color Information", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 17, no. , pp. 805-809, August 1995, doi:10.1109/34.400571
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