Topological pattern recognition and reconstruction from noise-affected boundary patterns

Chialun John Hu

doi:10.1117/12.758084

3 March 2008 Topological pattern recognition and reconstruction from noise-affected boundary patterns

Chialun John Hu

Proceedings Volume 6812, Image Processing: Algorithms and Systems VI; 68120R (2008) https://doi.org/10.1117/12.758084
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

Using our recently modified curve-fitting-topological-coding (CFTC) computer program, we can automatically obtain a precise topological code to represent the topological property of a closely reconstructed boundary of a selected object in an edge-detected picture. This topological property is perhaps the most important property to be used for object identification. It is very accurate, yet very robust, because the topological property is independent of geometrical location, shape, size, orientation, and viewing angles. It is very accurate if two different objects to be differentiated or to be identified have different boundary topologies. Patch noise and obscuring noise can also be automatically eliminated as shown in some live experiments.

Citation Download Citation

Chialun John Hu "Topological pattern recognition and reconstruction from noise-affected boundary patterns", Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68120R (3 March 2008); https://doi.org/10.1117/12.758084

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