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
- Binyaminu Usman Polytechnic, Hadijia, Jigawa State 3
- Borno State University, Maiduguri, Borno State 15
- Bowen University, Iwo, Osun State 1
- Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State 255
- College of Agriculture and Animal Science, Mando Road, Kaduna, Kaduna State 1
- College of Agriculture, Science and Technology, Lafia, Nasarawa State 8
- College of Education, Akwanga (affl To Ahmadu Bello Univ, Zaria) 1
- College of Education, Eha Amufu, (Affliliated To Unn), Enugu State 1
- College of Education, Warri (Affiliated To Delta State Uni, Abraka), Delta State 1
- College of Health Technology, Calabar, Cross River State 1