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
- Mohammed Lawan College of Agriculture, Maiduguri, Borno State 12
- Moshood Abiola Polytechnic, Abeokuta, Ogun State 7
- Nasarawa State University, Keffi, Nasarawa State 8
- Niger Delta University, Wilberforce Island, Bayelsa State 28
- Niger State College of Education, Minna, (Affl To Usmanu Danfodiyo Uni, Sokoto) 1
- Nigeria Maritime University, Okerenkoko, Delta State 1
- Nigerian Army University, Biu, Borno State 3
- Nile University of Nigeria, Abuja 3
- Nnamdi Azikiwe University, Awka, Anambra State 98
- Northwest University, Kano, Kano State 179