Method and device for automatic image segmentation by textural a

Image analysis – Histogram processing – For setting a threshold

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382 14, 382 15, 382 16, G06K 946

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053217713

ABSTRACT:
A device for automatic image segmentation according to the invention comprises a data processor associated with a network of automata organized in three levels; the inputs of each of the automata are weighted by adjustable coefficients; the number of automata of the first level is equal to the number of characteristic values computed from observation windows taken firstly in a set of examples of image zones having different textures. Learning by the network permits adjustment of the weighting coefficients of the automata of the network until all the examples of the same texture lead to the same configuration.

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patent: 5060277 (1991-10-01), Bokser
Araujo et al., A Parallel Architecture for Texture Analysis Based on the Concept of Associative Memory, Proceeding IEEE International Symposium on Intelligent Conrol, Aug. 24-26, 1988 ,pp. 633-637.
Glover, An Optical Fourier/Electronic Neurocomputer Automated Inspection System, IEEE International Conference on Neural Networks, Jul. 24-27, 1988, pp. 569-576.
Dupaguntla et al., A Neural Network Architecture for Texture Segmentation and Labelling, International Joint Conference on Neural Networks, Jun. 18-22, 1989, pp. 127-133.
Pattern Recognition Letters, vol. 2, No. 3, Mar. 1984, Elsevier Science Publishers B.V., (Amsterdam, NL), M. Unser et al.: "Feature extraction and decision procedure for automated inspection of texture materials", pp. 185-191 voir p. 186, col. 1, lignes 24-30, 34-36; p. 186, col. 2, lignes 26-36; p. 189, col. 1, lignes 5-9; p. 189, col. 2, lignes 18-22.
IEEE Proceedings on Pattern Recognition and Image Processing, Jun. 14-17, 1982, Las Vegas, Nevada, IEEE, (New York, US), A. K. C. Wong et al.: "Search-effective multi-class texture classification", pp. 208-213 voir abrege; p. 210, col. 2, lignes 39-45; p. 212, col. 1, lignes 34-40.

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