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Contour Extraction Based on Surround Inhibition and Contour Grouping

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Computer Vision – ACCV 2009 (ACCV 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5995))

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Abstract

Extraction of object contours from the natural scene is a difficult task because it is hard to distinguish between object contour and texture edge. To overcome this problem, this paper presents a contour extraction method inspired by visual mechanism. Firstly, a biologically motivated surround inhibition process, improved by us, is applied to detect contour elements. Then we utilize visual cortical mechanisms of perceptual grouping to propose a contour grouping model. This model consists of two levels. At low level, a method is presented to compute local interaction between contour elements; at high level, a global energy function is suggested to perceive salient object contours. Finally, contours having high energy are retained while the others, such as texture edge, are removed. Experimental results show our method works well.

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Li, Y., Zhang, J., Jiang, P. (2010). Contour Extraction Based on Surround Inhibition and Contour Grouping. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12304-7_65

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  • DOI: https://doi.org/10.1007/978-3-642-12304-7_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12303-0

  • Online ISBN: 978-3-642-12304-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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