Research on Surface Defect Detection Technique of Rolling Element Based on Computer Vision

Chuan Ren; Xiao Yu Xiu; Guo Hui Zhou

doi:10.4028/www.scientific.net/AMR.1006-1007.773

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1006-1007Research on Surface Defect Detection Technique of...

Research on Surface Defect Detection Technique of Rolling Element Based on Computer Vision

Abstract:

This paper proposed a new method of surface defect detection of rolling element based on computer vision, which adopted CCD digital camera as image sensor, and used digital image processing techniques to defect the surface defects of rolling element. The main steps include collect image, use an improved median filter to reduce the noise, increase or decrease the exposure to achieve the image enhancement, create a binary image with threshold method and detect the edge of the image, and use subtraction method for surface defects identification. The experiment indicates that the above methods the advantages of simple, the capability of noise resistance, high speed processing and better real-time.

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Periodical:

Advanced Materials Research (Volumes 1006-1007)

Pages:

773-778

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1006-1007.773

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Online since:

August 2014

Authors:

Chuan Ren, Xiao Yu Xiu, Guo Hui Zhou*

Keywords:

Computer Vision, Defect Detection, Edge Detection, Rolling Element, Surface Defects

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* - Corresponding Author

References

[1] R. C Gonzalez, R.E. Woods. Digital Image Processing, 2nd ed., New Jersey: Prentice-Hall. (2002).

Google Scholar

[2] N Aleixos, J Blasco, F Navarron, E Molto. Multispectral Inspection of Citrus in Real-time Using Machine Vision and Digital Signal Processors. Computers and Electronics in Agriculture. 33: 121-137, (2002).

DOI: 10.1016/s0168-1699(02)00002-9

Google Scholar

[3] Chang-Hsing Lee, Ling-Hwei Chen, Wei-Kang Wang. Image Contrast Enhancement Using Classified Virtual Exposure Image Fusion. IEEE Trans. Consumer Electron., vol. 58, no. 4, pp.1253-1261, Nov. (2012).

DOI: 10.1109/tce.2012.6414993

Google Scholar

[4] P.S. Liao, T.S. Chen, P.C. Chung. A Fast Algorithm for Multilevel Thresholding. J. Inform. Sci. Eng., vol. 17, no. 5, pp.713-727, (2001).

Google Scholar

[5] Hongbin Jia, Murphey Y.L., Jianjun Shi, Tzyy-Shuh Chang. An Intelligent Real-time Vision System for Surface Defect Detection. Proceedings of the 17th International Conference, vol. 3, pp.239-242, Aug. (2004).

DOI: 10.1109/icpr.2004.1334512

Google Scholar

[6] Hongtao Zhang, Fajie Duan, Keqin Ding. Development of Key Technology on Surface Defects Detection System for Steel Strip [J]. Acta Metrologica Sinica, 28(3): 216-219, (2007).

Google Scholar

[7] Xuanyin Wang, Dongtai Liang. Surface Defect Detection Based on Multivariate Image Analysis [J]. Journal of Zhejiang University (Engineering Science), vol. 44, no. 3, pp.448-452, Mar. (2010).

Google Scholar