Segmentation by Adaptive Prediction and Region Merging

Abstract This paper presents a segmentation technique based on prediction and adaptive region merging. While many techniques for segmentation exist, few of them are suited for the segmentation of natural images containing regular textures defined on non-rectangular segments. In this paper, we propose a description of regions based on a deconvolution algorithm whose purpose is to remove the influence of the shape on region contents. The decoupling of shape and texture information is achieved either by adapting waveforms to the segment shape, which is a time-consuming task that needs to be repeated for each segment shape, or by the extrapolation of a signal to fit a rectangular window, which is the chosen path. The deconvolution algorithm is the key of a new segmentation technique that uses extrapolation as a prediction of neighbouring regions. When the prediction of a region fits the actual content of a connected region reasonably well, both regions are merged. The segmentation proc...

• Type: Conference
• Year: 2003
• Where: DICTA
• Authors: Marc Van Droogenbroeck, Hugues Talbot
• Keywords: Deconvolution Algorithm, DICTA 2003, DICTA 2007, Natural Images, Segmentation Technique