| Autor: | Luis F. Chaparro, Jinsung Oh |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Artificial neural network
business.industry Applied Mathematics Binary image ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Image processing Mathematical morphology Impulse noise Fuzzy logic Structuring Computer Science Applications Filter design Artificial Intelligence Hardware and Architecture Signal Processing Computer vision Artificial intelligence business Software Information Systems Mathematics |
| Zdroj: | Multidimensional Systems and Signal Processing. 11:233-256 |
| ISSN: | 0923-6082 |
| DOI: | 10.1023/a:1008486530629 |
| Popis: | In this paper we first introduce a neural network implementation for fuzzy morphological operators, and by means of a training method and differentiable equivalent representations for the operators we then derive efficient adaptation algorithms to optimize the structuring elements. Thus we are able to design fuzzy morphological filters for processing multi-level or binary images. The convergence behavior of basic structuring elements and its significance for other structuring elements of different shape is discussed. Besides the filter design, the localized structuring elements obtained from the training method give a structural characterization of the image which is useful in many applications. The performance of the fuzzy morphological filters in removing impulse noise in multi-level and binary images is illustrated and compared with existing procedures. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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