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JSEG - Segmentation of color-texture regions in images and video


Yining Deng, B.S.Manjunath


The essential idea of JSEG is to separate the segmentation process into two independently processed stages, color quantization and spatial segmentation. In the first stage, colors in the image are quantized to several representing classes that can be used to differentiate regions in the image. This quantization is performed in the color space alone without considering the spatial distributions. Afterwards, image pixel colors are replaced by their corresponding color class labels, thus forming a class-map of the image. The main 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 "J-image", in which high and low values correspond to possible boundaries and interiors of color-texture regions. A region growing method is then used to segment the image based on the multi-scale J-images. For video sequences, a region tracking scheme is embedded into region growing and problems of motion estimation are avoided. The goal is to achieve consistent segmentation and tracking results, even for scenes with arbitrary non-rigid object motion. Experiments show the robustness of the JSEG algorithm on real images and video.


Both the original and the segmented images are shown in these examples.


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