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Improved Method for Gradient-Threshold Edge Detector Based on HVS

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

This paper presents an improved method which is suitable for gradient-threshold edge detectors. The proposed method takes into account the basic characteristics of the human visual system (HVS) and precisely determines the local masking regions for the edges with arbitrary shape according to the image content. Then the gradient image is masked with the luminance and the activity of local image before edge labelling. The experimental results show that the edge images obtained by our algorithm are more consistent with the perceptive edge images.

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References

  1. Ziou Djemel, D., Tabbone, S.: Edge detection techniques-an overview. Int. J. of Pattern Recognition and Image Analysis 8, 537–559 (1998)

    Google Scholar 

  2. Basu, M.: Gaussian-based edge-detection methods–a survey. IEEE Trans. Systems, Man, and Cybernetics-Part C 32, 252–260 (2002)

    Article  Google Scholar 

  3. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Machine Intell. 8, 679–698 (1986)

    Article  Google Scholar 

  4. Heath, M.D., Sarkar, S., Sanocki, T., Bowyer, K.W.: A robust visual method for assessing the relative performance of edge-detection algorithms. IEEE Trans. Pattern Anal. Machine Intell. 19, 1338–1358 (1997)

    Article  Google Scholar 

  5. Elmabrouk, A., Aggoun, A.: Edge detection using local histrogram analysis. Electronics letters 34, 1216–1217 (1998)

    Article  Google Scholar 

  6. Yang, F., Chang, Y., Wan, S.: Gradient-threshold edge detection based on HVS. Optical Engineering 44 (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. National Key Lab. on ISN, Xidian University, Xi’an, 710071, China

    Fuzheng Yang, Shuai Wan & Yilin Chang

Authors
  1. Fuzheng Yang
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  2. Shuai Wan
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  3. Yilin Chang
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Yang, F., Wan, S., Chang, Y. (2005). Improved Method for Gradient-Threshold Edge Detector Based on HVS. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_157

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  • DOI: https://doi.org/10.1007/11596448_157

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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