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Unsupervised watershed-driven region-based image retrieval

机译:无监督分水岭驱动的基于区域的图像检索

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摘要

A novel unsupervised strategy for content-based image retrieval is presented. It is based on a meaningful segmentation procedure that can provide proper distributions for matching via the earth mover's distance as a similarity metric. The segmentation procedure is based on a hierarchical watershed-driven algorithm that extracts meaningful regions automatically. In this framework, the proposed robust feature extraction and the many-to-many region matching along with the novel region weighting for enhancing feature discrimination play a major role. Experimental results demonstrate the performance of the proposed strategy.
机译:提出了一种新颖的基于内容的图像检索无监督策略。它基于有意义的分割程序,该程序可以提供适当的分布,以便通过推土机的距离作为相似性度量进行匹配。分割过程基于分层分水岭驱动的算法,该算法自动提取有意义的区域。在此框架中,所提出的鲁棒特征提取和多对多区域匹配以及用于增强特征识别的新型区域加权起着重要作用。实验结果证明了所提出策略的性能。

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