Colour segmentation with polynomial classification

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.

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