Title :
Self-organizing segmentation for house object
Author :
Lee, Moonju ; Lee, Sukhan
Author_Institution :
Dept. of Inf. & Commun. Eng., Sungkyunkwan Univ., Suwon, South Korea
Abstract :
Clustering is the basic and first step of a process in many different fields. Clustering has been researched for many years. K-means clustering method is one of famous algorithms. However it cannot determine how many clusters are needed. This algorithm overcomes a disadvantage of other clustering algorithms. This paper presents a new method. Our algorithm can choose clustering number automatically.
Keywords :
image segmentation; pattern clustering; house object; k-means clustering method; selforganizing segmentation; Clustering algorithms; Educational institutions; Image segmentation; Indexes; Object segmentation; Partitioning algorithms; Shape; Clustering; Segmentation;
Conference_Titel :
Control, Automation and Systems (ICCAS), 2011 11th International Conference on
Conference_Location :
Gyeonggi-do
Print_ISBN :
978-1-4577-0835-0