Enhancing JSEG Color Texture Segmentation Using Quaternion Algebra Method

Authors

  • Vijay Kumar Sharma Meerut Institute of Engineering and Technology
  • Owais Ahmad Shah Dayananda Sagar University
  • Kunwar Babar Ali Meerut Institute of Engineering and Technology
  • Ravi Kumar H. C. Dayananda Sagar Academy of Technology & Management
  • Ankita Chourasia Medicaps University
  • Mohammed Mujammil Ahmed Ghousia College of Engineering

DOI:

https://doi.org/10.12928/biste.v8i1.14743

Keywords:

Image Quantization, Quaternion, JSEG, Image Segmentation

Abstract

This work uses quaternion algebra to implement a unique color quantization method on the JSEG color texture segmentation. Typically, RGB color orientations in the composite hyper-planes are inverted to produce the key vectors of the color-space. Because quaternion algebra offers a highly logical way to work with homogeneous coordinates, color is represented as a quaternion in the proposed system. In this illustration, the color pixels are seen like in the 3D space such as point. The recommended model has resulted in a unique quantization method that uses level set techniques and projective geometry. This approach will be used in the JSEG color texture segmentation. This current color quantization technique is splintering clustering mechanism since it makes use of the binary quaternion moment preserving threshold technique. With this technique, color constancy throughout the spectrum and in the physical space are taken into account when they divide the color clusters located inside the RGB cube. The segmentation results are contrasted with JSEG and some of the recent established segmentation methods. These comparisons demonstrate how the proposed quantization approach strengthens the JSEG segmentation.

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Published

2026-01-31

How to Cite

[1]
V. K. Sharma, O. A. Shah, K. B. Ali, R. K. H. C., A. Chourasia, and M. M. Ahmed, “Enhancing JSEG Color Texture Segmentation Using Quaternion Algebra Method”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 8, no. 1, pp. 151–164, Jan. 2026.

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