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Hierarchical image analysis using irregular tessellations

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3 Author(s)
Montanvert, Annick ; Univ. Joseph Fourier, Grenoble, France ; Meer, P. ; Rosenfield, A.

A novel multiresolution image analysis technique based on hierarchies of irregular tessellations generated in parallel by independent stochastic processes is presented. Like traditional image pyramids these hierarchies are constructed in a number of steps on the order of log(image-size) steps. However, the structure of a hierarchy is adapted to the image content and artifacts of rigid resolution reduction are avoided. Two applications of these techniques are presented: connected component analysis of labeled images and segmentation of gray level images. In labeled images, every connected component is reduced to a separate root, with the adjacency relations among the components also extracted. In gray level images the output is a segmentation of the image into a small number of classes as well as the adjacency graph of the classes

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:13 ,  Issue: 4 )