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
- Federal Polytechnic, Mubi, Adamawa State 20
- Federal Polytechnic, Nasarawa, Nasarawa State 60
- Federal Polytechnic, Nekede, Imo State 53
- Federal Polytechnic, offa, Kwara State 19
- Federal Polytechnic, Oko, Anambra State 8
- Federal School of Biomedical Engineering, (LUTH), Idi-Araba, Lagos State 1
- Federal School of Surveying, Oyo, Oyo State 7
- Federal University of Agriculture, Abeokuta, Ogun State 19
- Federal University of Petroleum Resources, Effurun, Delta State 78
- Federal University of Technology Akure, Ondo State 23