Abstract
A new model of an adaptive adjacency graph (AAG) for representing a 2-D image or a 2-D view of a 3-D scene is introduced. The model makes use of image representation similar in form to a region adjacency graph. Adaptive adjacency graph, as opposed to region adjacency graph, is an active representation of the image. The AAG can adapt to the image or track features and maintain the topology of the graph. Adaptability of the AAG is achieved by incorporating active contours (`snakes') in the graph. Various methods for creating the AAGs are discussed. Results obtained for dynamic tracking of features in sequence of images and for registration of retinal images are presented.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Piotr Jasiobedzki "Adaptive adjacency graphs", Proc. SPIE 2031, Geometric Methods in Computer Vision II, (23 June 1993); https://doi.org/10.1117/12.146634
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Image segmentation

Computer vision technology

Image registration

Machine vision

3D modeling

3D image processing

Image restoration

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