Use of Quadtrees for Image Segmentation

Abstract
This paper examines an approach to image segmentation based on using a quadtree approximation image to identify regions in the image. The advantages of this approach are firstly that noise points are not present in the quadtree approximation of an image and secondly that by traversal of the tree it is possible to find the approximate location of the regions within an image. It is thus possible to extract a region by applying thresholds in the vicinity of the region and to identify the best threshold by correlating the extracted region with an edge map of the original image. Since thresholds to extract regions are applied locally, noise points which may be present elsewhere in the edge map have no effect on the correlation of extracted regions to the edge map of the original image.

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