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Image Segmentation Method Based Upon Otsu ACO Algorithm

  • Conference paper
Information and Automation (ISIA 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 86))

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Abstract

Image segmentation is a very important research content in the fields of computer vision and pattern recognition. As the basis for image understanding and image analysis it is always receives high attention. At present in those commonly used segmentation methods of contrast ratio, margin and grayscale detection the threshold processing is one of the most effective. The threshold methods can also be divided into Otsu, minimum error thresholding, optimum histogram entropy and minimum cross entropy, etc. By combining the advantages of ACO (Ant Colony Optimization) the present paper has designed an ACO segmentation algorithm of solving extra-class variance maximum value to determine the optimum threshold value. The algorithm can quickly and steadily find the optimum segmentation threshold in a non-linear way so as to effectively segment the target and its background, and receive a best result in image segmenting.

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Author information

Authors and Affiliations

  1. School of Computer Information Engineering, Shandong University of Finance, No. 40 Shungeng Road, 250014, Jinan, Shandong, China

    Kanglin Gao, Liqin Zhu & Mingjun Gao

  2. School of Information Science and Engineering, Jinan University, 250001, Jinan, Shandong, China

    Mei Dong

Authors
  1. Kanglin Gao
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  2. Mei Dong
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  3. Liqin Zhu
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  4. Mingjun Gao
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Editor information

Editors and Affiliations

  1. Wuhan Institute of Technology, Wuhan, Hubei, China

    Luo Qi

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Gao, K., Dong, M., Zhu, L., Gao, M. (2011). Image Segmentation Method Based Upon Otsu ACO Algorithm. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_85

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  • DOI: https://doi.org/10.1007/978-3-642-19853-3_85

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19852-6

  • Online ISBN: 978-3-642-19853-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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