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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Semi-supervised statistical region refinement for color image segmentation
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Semi-supervised statistical region refinement for color image segmentation

机译:用于彩色图像分割的半监督统计区域细化

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摘要

Some authors have recently devised adaptations of spectral grouping algorithms to integrate prior knowledge, as constrained eigenvalues problems. In this paper, we improve and adapt a recent statistical region merging approach to this task, as a non-parametric mixture model estimation problem. The approach appears to be attractive both for its theoretical benefits and its experimental results, as slight bias brings dramatic improvements over unbiased approaches on challenging digital pictures. (c) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
机译:一些作者最近设计了频谱分组算法的改编,以集成先验知识,作为受约束的特征值问题。在本文中,我们改进和适应了一种新的统计区域合并方法来完成此任务,作为非参数混合模型估计问题。这种方法似乎在理论上和实验结果上都具有吸引力,因为在偏爱的数字图片上,轻微的偏见会比无偏方法带来巨大的改进。 (c)2004模式识别学会。由Elsevier Ltd.出版。保留所有权利。

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