Recognition and Segmentation Method of Adhering Bars Based on Support Vector Machine

Guo Hua Liu; Bing Le Liu; Liang Yu Li

doi:10.4028/www.scientific.net/AMR.1082.491

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1082Recognition and Segmentation Method of Adhering...

Recognition and Segmentation Method of Adhering Bars Based on Support Vector Machine

Abstract:

This paper proposes a new solution to recognize and segment adhering bars. A support vector machine (SVM) is constructed according to the feature vectors of training samples to recognize the adhesions type of bars. The geometric feature values and moment feature values based on Blob regions in the image are extracted, which are the input feature vectors of support vector machine. The trained classifier is used for identifying the adhesions type of bars in the image. Finally, classification and recognition are realized by support vector machine. The experimental result shows that the recognition accuracy based RBF kernel achieves 100%. The method is feasible and effective for the recognition and segmentation of the adhering bars.

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Periodical:

Advanced Materials Research (Volume 1082)

Pages:

491-494

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1082.491

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Online since:

December 2014

Authors:

Guo Hua Liu*, Bing Le Liu, Liang Yu Li

Keywords:

Adhering Bars, Bars, Recognition, Segmentation, Support Vector Machine (SVM)

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* - Corresponding Author

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