Abstract
A new iterative method based on Support Vector Machines to perform automated colour adjustment processing in the automotive industry is proposed in this paper. The iterative methodology relies on a SVM trained with patterns provided by expert colourists and an actions' generator module. The SVM algorithm enables selecting the most adequate action in each step of an iterated feed-forward loop until the final state satisfies colorimetric bounding conditions. Both encouraging results obtained and the significant reduction of non-conformance costs, justify further industrial efforts to develop an automated software tool in this and similar industrial processes.
Original language | English |
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Publication status | Published - 22 Apr 2009 |
Event | European Symposium on Artificial Neural Networks, Bruges 2009 - Duration: 22 Apr 2009 → 24 Apr 2009 |
Conference
Conference | European Symposium on Artificial Neural Networks, Bruges 2009 |
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Period | 22/04/09 → 24/04/09 |