Abstract
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Article Information:
Kernel Selection of SVM for Commerce Image Classification
Lou Xiongwei and Huang Decai
Corresponding Author: Lou Xiongwei
Submitted: September 22, 2012
Accepted: November 12, 2012
Published: May 15, 2013 |
Abstract:
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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.
Key words: Commerce image classification, kernel selection, SVM, , , ,
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Cite this Reference:
Lou Xiongwei and Huang Decai, . Kernel Selection of SVM for Commerce Image Classification. Research Journal of Applied Sciences, Engineering and Technology, (20): 4850-4856.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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Sales & Services |
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