Review paper - Neural networks in image processing (moved)

Dear colleagues,


The frequently visited website on neural networks in image processing
has been moved to:


http://www.egmont-petersen.nl/nn-review.html


This website also contains a link to our review paper:


M. Egmont-Petersen, D. de Ridder, H. Handels. "Image processing with
neural networks - a review," Pattern Recognition, Vol. 35, No. 10, pp.
2279-2301, 2002.


Abstract:
We review more than two hundred 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 Hopfield neural networks. The various applications are

categorised into a novel two-dimensional taxonomy for image processing
algorithms. One dimension specifies 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 specific
constraints to a neural-based approach. These specific conditions are
discussed in detail. A synthesis is made of unresolved problems related

to application of pattern recognition techniques in image processing
and specifically to the application of neural networks. Finally, we
present an outlook into the future application of neural networks and
relate them to novel developments.


Keywords: neural network, digital image processing, invariant pattern
recognition, preprocessing, feature extraction, image compression,
segmentation, object recognition, image understanding, optimization,
survey.


Cheers,


Michael Egmont-Petersen

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