Picture segmentation with introducing an anisotropic preliminary step to an MRF model with cellular neural networks

Tamás Szirányi, László Czúni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Due to the large computation power needed for Markovian random field (MRF) based image processing, new variations of the basic MRF model are implemented. The transportation of the model to the very fast cellular neural networks (CNN) gave new tasks and opportunities to improve the technique, since the CNN has a special local architecture. This CNN architecture can be implemented in real VLSI circuits of superior speed in image processing. A type of MRF image segmentation with modified metropolis dynamics (MMD) can be well implemented in the CNN architecture. In this paper we address the improvement of this existing CNN method by introducing anisotropic diffusion as the smoothing process in the model. We suggest that this new feature with the MRF representation will give a new approach to solving early vision problems in the future.

Original languageEnglish
Title of host publicationTrack D
Subtitle of host publicationParallel and Connectionist Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages366-370
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - Jan 1 1996
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: Aug 25 1996Aug 29 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
CountryAustria
CityVienna
Period8/25/968/29/96

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Szirányi, T., & Czúni, L. (1996). Picture segmentation with introducing an anisotropic preliminary step to an MRF model with cellular neural networks. In Track D: Parallel and Connectionist Systems (pp. 366-370). [547447] (Proceedings - International Conference on Pattern Recognition; Vol. 4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.1996.547447