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Edge Detection Using Modified Directional Coefficient Mask in AWGN

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Future Information Communication Technology and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 235))

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Abstract

Image segmentation is required for the analysis of images and edge is one of the essential elements of image segmentation. Edge contains image information and it is applied in various fields of image processing. Typical methods of edge detection include Sobel, Prewitt and Roberts method and such methods have the advantage of simple realization and fast processing speed as they process images with mask in spatial area. However, when images are degraded by the addition of AWGN, an error of detecting edge in noise areas occur. Therefore, in this paper a new edge detection algorithm with excellent edge detection characteristics which effectively removes AWGN is proposed.

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Author information

Authors and Affiliations

  1. Department of Control and Instrumentation Engineering, Pukyong National University, Busan, Korea

    Chang-Young Lee & Nam-Ho Kim

Authors
  1. Chang-Young Lee
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  2. Nam-Ho Kim
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Corresponding author

Correspondence to Nam-Ho Kim .

Editor information

Editors and Affiliations

  1. , Computer Engineering, Paichai University, Baejae-ro, Seo-gu 155-40, Daejeon, 302-735, Korea, Republic of (South Korea)

    Hoe-Kyung Jung

  2. , Electronic Engineering, Mokwon University, Doanbookro, Seo-Ku 88, Daejeon, 302-729, Korea, Republic of (South Korea)

    Jung Tae Kim

  3. PO Box 2434, Electrical Engineering, QUT Gardens Point, George Street 2, Brisbane, 4001, Queensland, Australia

    Tony Sahama

  4. Normal University, Graduate Institute of Information, National Kaohsiung, No.116, Heping 1st Rd., Lingya District, Kaohsiung City, 80201, Kao-hsiung, Taiwan R.O.C.

    Chung-Huang Yang

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Lee, CY., Kim, NH. (2013). Edge Detection Using Modified Directional Coefficient Mask in AWGN. In: Jung, HK., Kim, J., Sahama, T., Yang, CH. (eds) Future Information Communication Technology and Applications. Lecture Notes in Electrical Engineering, vol 235. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6516-0_61

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  • DOI: https://doi.org/10.1007/978-94-007-6516-0_61

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6515-3

  • Online ISBN: 978-94-007-6516-0

  • eBook Packages: EngineeringEngineering (R0)

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