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International Journal of Research and Scientific Innovation (IJRSI)

An Analysis of Image Segmentation Techniques for Image Processing Applications

byS. Bhuvaneswari; M. Sulthan Ibrahim

Published March 31, 2026  •  Vol. 13, Issue 3, pp. 824–829Open Access
DOI: 10.51244/IJRSI.2026.1303000073

Abstract

Image processing techniques are a crucial component of modern computer technologies, playing a significant role in various applications such as the medical field, object detection, video surveillance systems, and computer vision. A key aspect of image processing is image segmentation, which involves dividing images into smaller parts known as segments. This process simplifies image representation to facilitate analysis. Numerous algorithms have been developed for image segmentation, each based on specific pixel features. This paper reviews and analyzes different segmentation algorithms, ultimately comparing them. Such a comparative study is valuable for enhancing the accuracy and performance of segmentation methods across various image processing domains.

Keywords: Image Segmentation, Digital Image Processing, K-Means Clustering

JournalInternational Journal of Research and Scientific Innovation (IJRSI)
ISSN2321-2705
Volume / IssueVolume 13, Issue 3
Pages824–829
Publication dateMarch 31, 2026
DOI10.51244/IJRSI.2026.1303000073
PublisherRSIS International
LicenseOpen Access

How to cite this article

S. Bhuvaneswari, & M. Sulthan Ibrahim (2026). An Analysis of Image Segmentation Techniques for Image Processing Applications. International Journal of Research and Scientific Innovation (IJRSI), 13(3), 824-829. https://doi.org/10.51244/IJRSI.2026.1303000073

BibTeX

@article{S2026,
  title   = {An Analysis of Image Segmentation Techniques for Image Processing Applications},
  author  = {S. Bhuvaneswari and M. Sulthan Ibrahim},
  journal = {International Journal of Research and Scientific Innovation (IJRSI)},
  volume  = {13},
  number  = {3},
  pages   = {824--829},
  year    = {2026},
  doi     = {10.51244/IJRSI.2026.1303000073},
  publisher = {RSIS International}
}