DocumentCode :
2277760
Title :
An improved segmentation algorithm of color image in complex background based on graph cuts
Author :
Hong, Hanyu ; Guo, Xiangyun ; Zhang, Xiuhua
Author_Institution :
Lab. for Image Process. & Intell. Control, Wuhan Inst. of Technol., Wuhan, China
Volume :
2
fYear :
2011
fDate :
10-12 June 2011
Firstpage :
642
Lastpage :
645
Abstract :
Recently, it is still difficult to extract interested object from complex background. In this field, interactive image segmentation method has attracted much attention in the vision. In this paper, we propose a new algorithm to segment the interested object from complex background. In the algorithm, we use the improved K-means clustering in the LUV color space to get more accurate classifications of the labeled pixels. Then, build up energy function model and calculate the energy of segmentation properly. Finally, we get the perfect result through graph cuts and denoising algorithm based on connected components.
Keywords :
graph theory; image colour analysis; image denoising; image segmentation; pattern clustering; K-means clustering; LUV color space; color image segmentation algorithm; complex background; denoising algorithm; energy function model; graph cuts; interactive image segmentation method; Billets; Classification algorithms; Clustering algorithms; Image color analysis; Image segmentation; Noise reduction; Pixel; K-means clustering; color image segmentation; complex background; energy function; graph cuts;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
Type :
conf
DOI :
10.1109/CSAE.2011.5952551
Filename :
5952551
Link To Document :
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