An Approach to Image Segmentation Using K-Means Clustering Algorithm
Student: Ayomide Emmanuel Olatunde (Project, 2025)
Department of Computer Engineering
Osun State Polytechnic, Iree, Osun State
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 continuity. 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: ayomideolatunde3@gmail.com
Filters
Institutions
- AVE-MARIA UNIVERSITY, PIYANKO, NASARAWA STATE 1
- Babcock University, Ilishan-Remo, Ogun State 7
- Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State 455
- Bauchi State College of Agriculture, Bauchi, Bauchi State 1
- Bauchi State University, Gadau, Bauchi State 16
- Bayelsa State Polytechnic, Aleibiri, Bayelsa State 13
- Bayero University, Kano, Kano State 587
- Benue State Polytechnic, Ugbokolo, Benue State 10
- Benue State University, Makurdi, Benue State 47
- Bingham University, Karu, Nasarawa State 3