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Impact of Using Different Color Spaces on the Image Segmentation

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The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) (AMLTA 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 113))

Abstract

Image segmentation is considered one of the most difficult challenges in image processing. Recently many advanced applications have emerged in this field. Color images provide more information and more reliable in segmentation than grayscale images. In this paper, the color spaces RGB, YCbCr, XYZ, and HSV are compared using four different methods of image segmentation. These methods are k-means, Fuzzy C-means, Region growing, and Graph Cut. The main objective of image segmentation is to simplify and change the image to something more meaningful and easier to analyze. In this study, we used single-color space components. In addition to this, we vote between the three components of every color space in the segmented image to get the best image segmentation result. Different RGB color images from Berkeley databases are used. The accuracy of the image segmentation is measured using the peak signal-to-noise ratio (PSNR) and mean square error (MSE). The experimental results show that the voting between color components achieved good segmentation accuracy.

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Author information

Authors and Affiliations

  1. Faculty of Science, Benha University, Banha, Egypt

    Dena A. Abdelsadek & Mosab Hassaan

  2. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Maryam N. Al-Berry & Hala M. Ebied

Authors
  1. Dena A. Abdelsadek
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  2. Maryam N. Al-Berry
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  3. Hala M. Ebied
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  4. Mosab Hassaan
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Corresponding author

Correspondence to Dena A. Abdelsadek .

Editor information

Editors and Affiliations

  1. Faculty of Computer and AI, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Port Said University, Port Fouad, Egypt

    Rawya Y. Rizk

  3. Department of Computer Science, VÅ B-TUO, Ostrava-Poruba, Czech Republic

    Václav Snášel

  4. Faculty of Engineering, Port Said University, Port Fouad, Egypt

    Rehab F. Abdel-Kader

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Abdelsadek, D.A., Al-Berry, M.N., Ebied, H.M., Hassaan, M. (2022). Impact of Using Different Color Spaces on the Image Segmentation. In: Hassanien, A.E., Rizk, R.Y., Snášel, V., Abdel-Kader, R.F. (eds) The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022). AMLTA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-031-03918-8_39

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