Fast Image Analysis using Kohonen Maps
D.Willett, C.Busch, F.Seibert
Artificial Neural Networks, Image Classification, Kohonen Feature Map, Nearest Neighbor Search
The paper considers image analysis with Kohonen Feature Maps. These types of
neural networks have proven their usefulness for pattern recognition in the
field of signal processing in various applications. The paper reviews a
classification approach, used in medical applications, in order to segment
anatomical objects such as brain tumors from magnetic resonance imaging (MRI)
data. The same approach can be used for environmental purposes, to derive
land-use classifications from satellite image data. These applications require
tremendous processing time when pixel-oriented approaches are
chosen. Therefore the paper describes implementation aspects which result in a
stunning speed-up for classification purposes. Most of them are based on
geometric relations in the feature-space.
The proposed modifications were tested on the mentioned
applications. Impressive speed-up times could be reached independent of
Proceedings of the IEEE Workshop NNSP, pp. 461-470, (1994)
A PostScript version, compressed with gzip, can be found here.
Last modified: Wed June 25 1997 11:39:34
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