Name
Abstract | ||
|---|---|---|
Clustering method has been applied in many fields, including data mining, machine learning, information retrieval, and image analysis. In this paper, we propose a visual clustering method based on the genetic algorithm (GA) and image manipulation. The proposed method automatically determines the number of clusters in a binary image without using distance measures. There are three processes of the proposed method, i.e., creating the object table, mapping the object table into a binary image, and clustering objects in the binary image by using the GA and image manipulation. The effectiveness of the proposed method is tested on both synthetic data sets and a real data set. The experimental results show that the proposed method can effectively construct the clusters in both synthetic and real data sets. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISPACS.2011.6146206 | Intelligent Signal Processing and Communications Systems |
Keywords | Field | DocType |
genetic algorithms,image processing,pattern clustering,binary image,data mining,genetic algorithm,image analysis,image manipulation,information retrieval,machine learning,synthetic data sets,visual clustering method,clustering method,data clustering,genetic algorithm,visual clustering | Computer vision,Fuzzy clustering,Canopy clustering algorithm,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Pattern recognition,Computer science,Binary image,Consensus clustering,Artificial intelligence,Cluster analysis | Conference |
ISBN | Citations | PageRank |
978-1-4577-2165-6 | 1 | 0.35 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ukrit Marung | 1 | 1 | 0.35 |
| Nipon Theera-umpon | 2 | 184 | 30.59 |
| S. Auephanwiriyakul | 3 | 246 | 39.45 |