Cell Blood Image Segmentation Based on Genetic Algorithm

  • A. Y. Ayoub
  • M. A. El-ShorbagyEmail author
  • I. M. El-Desoky
  • A. A. Mousa
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1153)


There are many methods of clustering that have been used to divide images. k-means algorithm is considered the most popular method of cluster analysis. Due to disadvantages of k-means algorithm, in this paper, the image is segmented using modified genetic algorithm (GA) by k-means algorithm; where k-means is used as an initialization of GA. The proposed algorithm was applied to several of cell blood images from microscope and the results showed that the value of PSNR for the proposed algorithm is higher than other algorithms, which indicates its efficiency in image segmentation.


Image segmentation Genetic algorithm Cluster analysis k-means algorithm 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • A. Y. Ayoub
    • 1
  • M. A. El-Shorbagy
    • 1
    • 2
    Email author
  • I. M. El-Desoky
    • 1
  • A. A. Mousa
    • 1
    • 3
  1. 1.Department of Basic Engineering Science, Faculty of EngineeringMenoufia UniversityShebin El-KomEgypt
  2. 2.Department of Mathematics, College of Science and Humanities in Al-KharjPrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia
  3. 3.Mathematics and Statistics Department, College of ScienceTaif UniversityTaifSaudi Arabia

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