An Approach to Image Segmentation Using K-Means Algorithm
Student: Victor Ejeh Jacob (Project, 2025)
Department of Computer Engineering
Osun State Polytechnic, Iree, Osun State
Abstract
ABSTRACT
This project proposes a color-based segmentation method that uses K-means clustering technique. The k-means algorithm is an iterative technique used to partition an image into k clusters. The standard K-Means algorithm produces accurate segmentation results only when applied to images defined by homogenous regions with respect to texture and color since no local constraints are applied to impose spatial contimity. At first, the pixels are clustered based on their color and spatial features, where the clustering process is accomplished. Then the clustered blocks are merged to a specific number of regions. This approach thus provides a feasible new solution for image segmentation which may be helpful in image retrieval.
Keywords
For the full publication, please contact the author directly at: victorjacob461@gmail.com
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Institutions
- Novena University, Ogume, Delta State 1
- Nuhu Bamalli Polytechnic, Zaria, Kaduna State 7
- Nwafor Orizu College of Education, Nsugbe, Anambra State 1
- Obafemi Awolowo University, Ile-Ife, Osun State 15
- Oduduwa University, Ipetumodu, Osun State 9
- Ogun State College of Health Technology, Ilese-Ijebu, Ogun State 1
- Ogun State Institute of Tech(formerly Gateway Ict Poly), Igbesa, Ogun State 4
- Olabisi Onabanjo University, Ago-Iwoye, Ogun State 38
- Ondo State University of Medical Sciences, Laje Road, Ondo, Ondo State 1
- Osun State College of Education, Ila-Orangun 1