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2013 (Vol. 5, Issue: 20)
Article Information:

Kernel Selection of SVM for Commerce Image Classification

Lou Xiongwei and Huang Decai
Corresponding Author:  Lou Xiongwei 

Key words:  Commerce image classification, kernel selection, SVM, , , ,
Vol. 5 , (20): 4850-4856
Submitted Accepted Published
September 22, 2012 November 12, 2012 May 15, 2013
Abstract:

Content-based image classification refers to associating a given image to a predefined class merely according to the visual information contained in the image. In this study, we employ SVM (Support Vector Machine) and presented a few kernels specifically designed to deal with the problem of content-based image classification. Several common kernel functions are compared for commerce image classification with the PHOW (Pyramid Histogram of visual Words) descriptors. The experiment results illustrate that chi-square kernel and histogram intersection kernel are more effective with the histogram based image descriptor for commerce image classification.
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  Cite this Reference:
Lou Xiongwei and Huang Decai, 2013. Kernel Selection of SVM for Commerce Image Classification.  Research Journal of Applied Sciences, Engineering and Technology, 5(20): 4850-4856.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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