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7 The goal of the presented change detection algorithm is to extract objects that appear in only one of two input images. A typical application is surveillance, where a scene is captured at different times of the day or even on different days. In this 9 paper we assume that there may be a significant noise or illumination differences between the input(More)
function or by a vector of features. In this paper we present a new method for texture characterization, which is based For a given textured image we define a sequence of graphs hNs(t)js[I (called MRCG), where Ns(t) is the number of 4-conon topological properties at different gray-levels and differnected components with size $s, for the images thresholded(More)
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