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2012 (Vol. 4, Issue: 01)
Article Information:

Tire Defect Detection Using Image Component Decomposition

Qiang Guo and Zhenwen Wei
Corresponding Author:  Qiang Guo 

Key words:  Defect detection, image decomposition, local total variation, the wavelet transform, , ,
Vol. 4 , (01): 41-44
Submitted Accepted Published
2011 September, 02 2011 September, 30 2012 January, 01

This study presents a component decomposition based method for fast tire defect detection, which is motivated by the fact that defective tire images mainly consist of three components: texture, background and defect. Thus the proposed method exploits three steps to separate the defect component from the defective image. At the first step, the local total variation filtering is used to extract the texture. Then the background is estimated by the vertical mean filtering. Finally, the defect is detected by thresholding the residual image. Experimental results show that the proposed method is more accurate in locating the defects.
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  Cite this Reference:
Qiang Guo and Zhenwen Wei, 2012. Tire Defect Detection Using Image Component Decomposition.  Research Journal of Applied Sciences, Engineering and Technology, 4(01): 41-44.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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