DocumentCode :
3059816
Title :
Colour segmentation with polynomial classification
Author :
Bartneck, N. ; Ritter, W.
Author_Institution :
Res. Inst. for Inf. Technol., Daimler-Benz AG, Ulm, Germany
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
635
Lastpage :
638
Abstract :
An important step for image analysis is the reduction of colour levels to a small number of significant levels. This can be considered as a classification task. In this paper questions of suitable colour spaces are discussed, which have a strong correlation to the feature space used for classification. Furthermore polynomial classification as a method for colour segmentation with supervised learning is introduced. Finally results are shown coming from the application fields of traffic sign recognition and postal automation
Keywords :
feature extraction; image segmentation; learning (artificial intelligence); colour levels; feature space; image analysis; polynomial classification; postal automation; supervised learning; traffic sign recognition; Automation; Image analysis; Image color analysis; Image recognition; Image segmentation; Information analysis; Polynomials; Postal services; Space technology; Supervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2915-0
Type :
conf
DOI :
10.1109/ICPR.1992.201857
Filename :
201857
Link To Document :
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