Visual clustering method using genetic algorithm and image manipulation
Ukrit Marung, Nipon Theera‐Umpon, Sansanee Auephanwiriyakul · 2011
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.