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dc.titleAutomatic Produce Classification From Images Using Color, Texture And Appearance Cuespt
unicamp.authorRocha, A., Institute of Computing, University of Campinas (Unicamp), 13084-851, Campinas, SP, Brazilpt
unicamp.authorHauagge, D.C., Institute of Computing, University of Campinas (Unicamp), 13084-851, Campinas, SP, Brazilpt
unicamp.authorWainer, J., Institute of Computing, University of Campinas (Unicamp), 13084-851, Campinas, SP, Brazilpt
unicamp.authorGoldenstein, S., Institute of Computing, University of Campinas (Unicamp), 13084-851, Campinas, SP, Brazilpt
dc.description.abstractWe propose a system to solve a multi-class produce categorization problem. For that, we use statistical color, texture, and structural appearance descriptors (bag-of--features). As the best combination setup is not known for our problem, we combine several individual features from the state-of-the-art in many different ways to assess how they interact to improve the overall accuracy of the system. We validate the system using an image data set collected on our local fruits and vegetables distribution center. © 2008 IEEE.en
dc.relation.ispartofProceedings - 21st Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI 2008pt_BR
dc.identifier.citationProceedings - 21st Brazilian Symposium On Computer Graphics And Image Processing, Sibgrapi 2008. , v. , n. , p. 3 - 10,
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