Title :
Visual clustering method using genetic algorithm and image manipulation
Author :
Marung, Ukrit ; Theera-Umpon, Nipon ; Auephanwiriyakul, Sansanee
Author_Institution :
Dept. of Electr. Eng., Chiang Mai Univ., Chiang Mai, Thailand
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.
Keywords :
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;
Conference_Titel :
Intelligent Signal Processing and Communications Systems (ISPACS), 2011 International Symposium on
Conference_Location :
Chiang Mai
Print_ISBN :
978-1-4577-2165-6
DOI :
10.1109/ISPACS.2011.6146206