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
- Redeemers University, Ede, Osun State 4
- Rhema University, Aba, Abia State 11
- Rivers State University of Science and Technology, Port Harcourt, Rivers State 3
- RIVERS STATE UNIVERSITY, PORT HARCOURT, RIVERS STATE 13
- Rufus Giwa Polytechnic, Owo, Ondo State 2
- Saadatu Rimi College of Edu, Kumbotso, Kano State (affiliated To Abu, Zaria) 1
- Salem University, Lokoja, Kogi State 4
- School of Health Information Mgt (Uch, Ibadan), Oyo State 5
- School of Health Information Mgt, Oau Teaching Hospital, Ile-Ife, Osun State 30
- Skyline University Nigeria, Kano, Kano State 2