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Proceedings Paper

FAZYTAN - A System For Automated Image Evaluation.
Author(s): P. Schwarzmann; R. Erhardt; W. Kringler; W. Schlipf; E. Blanz; E. R. Reinhardt
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Paper Abstract

FAZYTAN has been designed and realized for systematic adaption to image evaluation problems, which can be characterized as classification tasks with the availability of a labeled training set of statistic relevant examples of the problem. The basic ideas of FAZYTAN are characterized by the cue words: - Processor oriented algorithms for digital image transformations (local neighborhood operations) and feature extraction (Minkowski measures) - Problem oriented systematic optimization procedures for image transformation and feature extraction steps - No restrictions to process large feature sets for difficult classification problems - High data throughput by application of TV-frame oriented subprocessors for image-transformation and feature extraction to attack voluminous classification tasks. Examples of applications of FAZYTAN in the fields of biologic cell analysis, object segmentation, texture analysis and satellite image analysis will be presented.

Paper Details

Date Published: 9 January 1984
PDF: 9 pages
Proc. SPIE 0435, Architectures and Algorithms for Digital Image Processing, (9 January 1984); doi: 10.1117/12.936991
Show Author Affiliations
P. Schwarzmann, University of Stuttgart (FRG)
R. Erhardt, University of Stuttgart (FRG)
W. Kringler, University of Stuttgart (FRG)
W. Schlipf, University of Stuttgart (FRG)
E. Blanz, University of Stuttgart (FRG)
E. R. Reinhardt, University of Stuttgart (FRG)


Published in SPIE Proceedings Vol. 0435:
Architectures and Algorithms for Digital Image Processing
Per-Erik Danielsson; Andre J. Oosterlinck, Editor(s)

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