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Histogram Based Color Object Classification by Multi-class Support Vector Machine

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Advanced Intelligent Computing (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6838))

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Abstract

This work presents a histogram based color object classification by SVM for laboratory automation. In the laboratory environment, existing problem is the classification of color objects which is understood as blob like pictures by the system via a camera. This automated system is located at hospitals, blood banks where we introduce the system different blood samples for different research purposes. The blood samples for different research purposes are realized with different colors of tube caps. These caps constitute the main problem here since their images are often blob like pictures. The segmented, multi color cap pictures are investigated in this paper by SVM for color object classification. To validate the performance of the system with SVM method, its output also compared to the other classification methods. In the future work different color spaces will be incorporated with SVM for better color classification.

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De-Shuang Huang Yong Gan Vitoantonio Bevilacqua Juan Carlos Figueroa

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© 2011 Springer-Verlag Berlin Heidelberg

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Mumcu, T.V., Aliskan, I., Gulez, K., Tuna, G. (2011). Histogram Based Color Object Classification by Multi-class Support Vector Machine. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_29

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  • DOI: https://doi.org/10.1007/978-3-642-24728-6_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24727-9

  • Online ISBN: 978-3-642-24728-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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