Title : 
Colour segmentation with polynomial classification
         
        
            Author : 
Bartneck, N. ; Ritter, W.
         
        
            Author_Institution : 
Res. Inst. for Inf. Technol., Daimler-Benz AG, Ulm, Germany
         
        
        
            fDate : 
30 Aug-3 Sep 1992
         
        
        
        
            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;
         
        
        
        
            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
         
        
        
            DOI : 
10.1109/ICPR.1992.201857