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Image processing with neural networks—a review

✍ Scribed by M. Egmont-Petersen; D. de Ridder; H. Handels

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
174 KB
Volume
35
Category
Article
ISSN
0031-3203

No coin nor oath required. For personal study only.

✦ Synopsis

We review more than 200 applications of neural networks in image processing and discuss the present and possible future role of neural networks, especially feed-forward neural networks, Kohonen feature maps and Hopÿeld neural networks. The various applications are categorised into a novel two-dimensional taxonomy for image processing algorithms. One dimension speciÿes the type of task performed by the algorithm: preprocessing, data reduction=feature extraction, segmentation, object recognition, image understanding and optimisation. The other dimension captures the abstraction level of the input data processed by the algorithm: pixel-level, local feature-level, structure-level, object-level, object-set-level and scene characterisation. Each of the six types of tasks poses speciÿc constraints to a neural-based approach. These speciÿc conditions are discussed in detail. A synthesis is made of unresolved problems related to the application of pattern recognition techniques in image processing and speciÿcally to the application of neural networks. Finally, we present an outlook into the future application of neural networks and relate them to novel developments.

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