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Image Segmentation Using Genetic Algorithm and OTSU

  • Jyotika Pruthi
  • Gaurav Gupta
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 437)

Abstract

Image Segmentation exists as a challenge that aims to extract the information from the image, making it simpler to analyze. There are some major issues associated with the conventional segmentation approaches. To come up with an improvised solution, image segmentation can be modeled as a nonlinear optimization problem which is also very difficult to be solved as global optimization. So to deal with this problem, we present metaheuristic algorithm namely Genetic Algorithm and its combination with OTSU giving the better results. These results have been analyzed with the help of parameters namely Threshold values, CPU Time and Region Non Uniformity.

Keywords

Metaheuristic Genetic algorithm OTSU Non linear optimization 

References

  1. 1.
    Otsu, N.: A threshold selection method from gray-level histogram. IEEE Trans. Syst. Man Cybern. 9, 62–66 (1979)CrossRefGoogle Scholar
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    Zanaty, EA, Ghiduk, A.S.: A novel approach based on genetic algorithms and region growing for magnetic resonance image (MRI) segmentation. J. Comput. Sci. Inform. Syst. (ComSIS), 10(3). doi: 10.2298/CSIS120604050Z(2013)
  3. 3.
    Maulik, U.: Medical image segmentation using genetic algorithms. IEEE Trans. Informa. Technol. Biomed. 13(2) (2009)Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceThe Northcap UniversityGurgaonIndia
  2. 2.Department of Applied SciencesThe Northcap UniversityGurgaonIndia

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