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We present efficient graph cut algorithms for three problems: (1) finding a region in an image, so that the histogram (or distribution) of an image feature within the region most closely matches a given model; (2) cosegmentation of image pairs and (3) interactive image segmentation with a user-provided bounding box. Each algorithm seeks the optimum of a global cost function based on the Bhattacharyya measure, a convenient alternative to other matching measures such as the Kullback-Leiblerdoi:10.1109/tpami.2014.2382104 pmid:26353126 fatcat:t2tk3mteszbvnoap6pohjt2g7i