21 March 1989 Regularity Detection As A Strategy In Object Modelling And Recognition
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Human subjects easily perceive and extensively use shape regularities such as symmetry or periodicity when they are confronted with the task of object description and recognition. A computer vision algorithm is presented which emulates such behaviour in that it similarly makes use of shape redundancies for the concise description and meaningful segmentation of object contours. This can be compared with the way in which designers proceed in using CAD/CAM. In order to make the problem more accessible to computer programming, the contours are analyzed in so-called 'arc length space'. This novel mapping facilitates the detection and elimination of regularities under a broad range of viewing conditions and yields a natural basis for the formulation of the corresponding model compression rules. Several of the regularities which have traditionally been treated separately, are given a unified substrate.
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L. Van Gool, J. Wagemans, A. Oosterlinck, "Regularity Detection As A Strategy In Object Modelling And Recognition", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); doi: 10.1117/12.969266; https://doi.org/10.1117/12.969266

Image segmentation


Information theory

Evolutionary algorithms

Artificial intelligence


Object recognition

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