A Novel Method of Wire Detection Combined PCNN with HT

Guang Han; Miao Zhang; Ying Chun Zhong; Li Xing Wei

doi:10.4028/www.scientific.net/AMR.139-141.2072

Paper Titles

The Study of the Relationship between the Helix and the Individual Error in Gear Hob Measurements
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Visual Technique for Detecting Weld Position Based on Hough Transformation
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Uncertainty Estimation in Straightness Mini-Zone Verification Based on Improved GPS Standard System
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Machine Vision System for Inspecting Surgical Blades
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A Novel Method of Wire Detection Combined PCNN with HT
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A Fast and Precise Measuring Method for Large Workpiece Based on Machine Vision
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Application of Machine Vision Technique in Plate Camber Control System
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Measurement Method for the Symmetry Error of Double Keyway in a Wheel Hub Bore
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Research of Welding Deformation Measurement Based on Visual Method
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 139-141A Novel Method of Wire Detection Combined PCNN...

A Novel Method of Wire Detection Combined PCNN with HT

Abstract:

The traditional method of wire detection is implemented artificially, and that is heavy-worked, inefficient and low-accurate. This paper proposes a novel method to complete the job by using image technology to improve production efficiency and product qualification rate. In this paper, Pulse Coupled Neuron Network (PCNN) has been applied to the wire image preprocessing, and then Hough Transform (HT) is used to extract features of lines, and detect them according to these features from the processed image. After that, whether the wires were qualified was determined by the criterion of parallelism and isometry. Comparison between different wire images was given in the experimental study. Experimental results showed that the proposed method was feasible and this method could achieve higher detection accuracy and efficiency compared with the traditional method.

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Periodical:

Advanced Materials Research (Volumes 139-141)

Pages:

2072-2075

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.139-141.2072

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Online since:

October 2010

Authors:

Guang Han, Miao Zhang, Ying Chun Zhong, Li Xing Wei

Keywords:

Hough Transform (HT), Image Preprocessing, Pulse Coupled Neuron Network (PCNN), Wire Detection

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References

[1] M.Y. Lai, L.L. Wang: Robotics and Computer-Integrated Manufacturing. Vol. 24 (2008) No. 2, pp.217-227.

Google Scholar

[2] J. Ge, Y.N. Wang, H. Zhang and B.W. Zhou: Chinese Journal of Scientific Instrument. Vol. 30 (2009) No. 9, pp.1866-1873 (In Chinese).

Google Scholar

[3] R. Eckhorn, H. J. Reitboeck, M. Arndt and P. Dicke: Neural Computation. Vol. 2 (1990) No. 3, pp.293-307.

Google Scholar

[4] G. Kuntimad, H.S. Ranganath: IEEE Transactions on Neural Network. Vol. 10 (1999) No. 3, pp.591-598.

Google Scholar

[5] X. Gu, D. Yu and L. Zhang: Pattern Recognition Letters. Vol. 25 (2004) No. 9, pp.1075-1084.

Google Scholar

[6] L. Shang, Z. Yi and L. Ji: Neural Processing Letters. Vol. 25 (2007) No. 1, pp.49-62.

Google Scholar

[7] R.O. Duda and P.E. Hart: Communication of the ACM. Vol. 15 (1972) No. 1, pp.11-15.

Google Scholar

[8] T. Risse: Computer Vision, Graphics, and Image Processing. Vol. 46 (1989) No. 3, pp.327-345.

Google Scholar