Title :
Image segmentation algorithm based on feature fusion and cluster
Author :
Zhanguo Gao ; Li Yao ; Fengyu Duan
Author_Institution :
Coll. of Inf. Technol., Beihua Univ., Jilin, China
Abstract :
In order to make balance between the effect and time consumption of image segmentation, an image segmentation algorithm based on feature fusion and cluster is proposed in this paper. Firstly, the segmentation granularity is obtained adaptively according to the coarseness of image; secondly, different features are extracted, multi features are fused and classified by K-means clustering, and the image can be segmented quickly. Experiments show that the proposed algorithm can segment image quickly, and the segmentation effect is good, which has verified the validity.
Keywords :
feature extraction; image segmentation; pattern clustering; feature cluster; feature extraction; feature fusion; image coarseness; image segmentation algorithm; k-means clustering; segmentation granularity; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Feature extraction; Image color analysis; Image segmentation; Signal processing algorithms; Clustering; Feature Fusion; Image Segmentation;
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
DOI :
10.1109/MEC.2011.6025655
