Title :
An automatic color textured image segmentation algorithm using mean histogram features
Author :
Rahman, Md Mahbubur
Author_Institution :
Comput. Sci. & Eng. Discipline, Khulna Univ., Khulna, Bangladesh
Abstract :
A new integrated feature distributions based color textured image segmentation algorithm has been proposed. The proposed scheme uses histogram based new color texture extraction method which inherently combines color texture features rather then explicitly extracting it. Use of non parametric Bayesean clustering makes the segmentation framework fully unsupervised where no a priori knowledge about the number color textures regions are required. The feasibility and effectiveness of the proposed method have been demonstrated by various experiments using color textured images. The experimental results reveal that superior segmentation results can be obtained through the proposed unsupervised segmentation framework.
Keywords :
Bayes methods; feature extraction; image colour analysis; image segmentation; image texture; Bayesian clustering; automatic color textured image segmentation algorithm; color texture extraction; color texture feature; feature distribution based color textured image segmentation algorithm; mean histogram feature; unsupervised segmentation framework; Color texture feature; Image segmentation; Mean histogram; Non parametric Bayesian clustering;
Conference_Titel :
Electrical and Computer Engineering (ICECE), 2010 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4244-6277-3
DOI :
10.1109/ICELCE.2010.5700788