Skip to Main content Skip to Navigation
Conference papers

Unsupervised Segmentation of Color Images

Abstract : A novel technique for unsupervised learning in feature space is presented. The feature space is considered as composed of two distinct sources, “mode” and “valley”, in the point of view of information theory. An entropy-based thresholding is taken to distinguish the discretized cells in the feature space. The cells labeled as “mode” are then chained to form mode areas. Thereafter a modified Akaike's information criterion is proposed to solve the cluster validity problem. After all the parameters are estimated, a labeling algorithm is developed based on the majority game theory. The method is applied to color image segmentation. The segmentation process is completely autonomous
Document type :
Conference papers
Complete list of metadata
Contributor : Shan Yu Connect in order to contact the contributor
Submitted on : Thursday, November 27, 2014 - 4:31:01 AM
Last modification on : Friday, February 4, 2022 - 3:18:20 AM




Guodong Guo, Shan yu, Songde Ma. Unsupervised Segmentation of Color Images. ICIP 1998 - International Conference on Image Processing, Oct 1998, Chicago, United States. ⟨10.1109/ICIP.1998.727203⟩. ⟨hal-01087883⟩



Record views