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Image Threshold Segmentation Technology Research Based on Adaptive Genetic Algorithm

  • Deying Gu
  • Zhiliang Ren
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 99)

Abstract

On the basis of the OTSU methods study, the paper introduced adaptive genetic algorithm to optimize algorithm and achieve image segmentation. Experiment shows that the speed of the algorithm improves and the quality of segmentation is better. Lay the foundation for image recognition in the following.

Keywords

Image Segmentation Adaptive Genetic Algorithm OTSU Method 

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References

  1. 1.
    Zheng, Y.J.: A Survey on Evaluation Methods for Image Segmentation. Pattern Recognition 29(8), 346–352 (1996)Google Scholar
  2. 2.
    Wu, Y.Q.: The Progress of Methods for Image Threshold Selection in Last Thirty Years (1962-1992). Journal of Data Acquisition & Procession 8(3), 193–201 (1993)Google Scholar
  3. 3.
    Huang, J.X., Liu, H., Huang, W.: A Threshold Selection Method of Image Segmentation Based on Genetic Algorithms. Journal of Nanjing Normal University (Engineering and Technology Edition) 7(1), 14–17 (2007)zbMATHGoogle Scholar
  4. 4.
    Goldberg, D.: Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley, Pearson, Reading, MA (1989)zbMATHGoogle Scholar
  5. 5.
    Guo, Z., Chen, Y.Z.: Research of Threshold Methods for Image Segmentation. Journal of Communication University of China (Science and Technology) 115(2), 77–82 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Deying Gu
    • 1
  • Zhiliang Ren
    • 2
  1. 1.Northeastern UniversityQinhuangdaoChina
  2. 2.Northeastern UniversityShenyangChina

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