AN OPTIMAL REGION GROWING ALGORITHM FOR IMAGE SEGMENTATION

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Abstract
We present a new approach to the segmentation problem by optimizing a criterion which estimates the quality of a segmentation. We use a graph-based description of a partition of an image and a merging strategy based on the optimal use of a sequence of criteria. This method separates the strategy of making use of the segmentation criteria from their definition. An efficient data structure enables our implementation to have a low algorithmic complexity. Our method offers a general framework for solving a large class of segmentation problems. We show how to adapt this method to segment 2-D natural images including color images. This algorithm is also used for segmentation of 3-D images.