Title :
A semi-supervised color image segmentation method
Author :
Qian, Yuntao ; Si, Wenwu
Author_Institution :
Sch. of Comput. Sci., Zhejiang Univ., Hangzhou, China
Abstract :
A new color image segmentation algorithm based on semi-supervised clustering is proposed, which integrates limited human assistance, a user indicates the relationship of some different regions in an image by mouse, to get the final accurate segmentation result which satisfies the prior segmentation constraints. The algorithm first has the image quantified and then clusters in the quantified color space with prior segmentation information. Experiment results show that the proposed algorithm is effective and has high value of utility.
Keywords :
image colour analysis; image segmentation; learning (artificial intelligence); human assistance; quantified color space; semisupervised clustering; semisupervised color image segmentation method; Clustering algorithms; Color; Humans; Image retrieval; Image segmentation; Layout; Machine vision; Mice; Pixel; Semisupervised learning; EM algorithm; clustering; image segmentation; semi-supervised learning;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530275
