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Unsupervised Segmentation of Color-Texture Regions in Images and Video (2001)
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BibTeX
@MISC{Manjunath01unsupervisedsegmentation,
author = {B. S. Manjunath and Yining Deng and Yining Deng},
title = {Unsupervised Segmentation of Color-Texture Regions in Images and Video},
year = {2001}
}
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Abstract
A new method for unsupervised segmentation of color-texture regions in images and video is presented. This method, which we refer to as JSEG, consists of two independent steps: color quantization and spatial segmentation. In the first step, colors in the image are quantized to several representative classes that can be used to differentiate regions in the image. The image pixels are then replaced by their corresponding color class labels, thus forming a class-map of the image. The focus of this work is on spatial segmentation, where a criterion for "good" segmentation using the class-map is proposed. Applying the criterion to local windows in the class-map results in the "Jimage, " in which high and low values correspond to possible boundaries and interiors of colortexture regions. A region growing method is then used to segment the image based on the multiscale J-images. A similar approach is applied to video sequences. An additional region tracking scheme is embedded into the region growing process to achieve consistent segmentation and tracking results, even for scenes with non-rigid object motion. Experiments show the robustness of the JSEG algorithm on real images and video.
Keyphrases
color-texture region spatial segmentation real image new method several representative class image pixel non-rigid object motion independent step colortexture region color quantization possible boundary jseg algorithm good segmentation class-map result local window consistent segmentation corresponding color class label additional region multiscale j-images unsupervised segmentation first step low value similar approach
