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 University of Technology, Minna, Niger State 47
- Federal University of Technology, Owerri, Imo State 95
- Federal University Oye-Ekiti, Ekiti State 41
- Federal University, Birnin-Kebbi, Kebbi State 37
- Federal University, Dutse, Jigawa State 6
- Federal University, Dutsin-Ma, Katsina State 63
- Federal University, Gashua, Yobe State 3
- Federal University, Gusau, Zamfara State 14
- Federal University, Kashere, Gombe State 1
- Federal University, Lafia, Nasarawa State 6