首页> 外文期刊>International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems >CONTENT-BASED IMAGE RETRIEVAL OF KAOU IMAGES BY RELAXATION MATCHING OF REGION FEATURES
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CONTENT-BASED IMAGE RETRIEVAL OF KAOU IMAGES BY RELAXATION MATCHING OF REGION FEATURES

机译:通过区域特征的松弛匹配检索基于图像的考夫图像

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摘要

An improvement to the content-based image retrieval (CBIR) system for kaou images which has been developed by the authors group is introduced. Kaous are handwritten monograms found on old Japanese documents in a Chinese character-like shapes with artistic decorations. Kaous play an important role in the research of historical documents, which involve browsing and comparison of numerous samples. In this work, a novel method of kaou image modeling for CBIR is introduced, which incorporates the shade information of a closed kaou region in addition to the conventionally used contour characteristics. Dissimilarity of query and dictionary images were calculated as a weighted sum of elementary differences in the positions, contour shapes and colors of the component regions. These elementary differences were evaluated using relaxation matching and empirically defined distance functions. In the experiments, a set of 2455 kaou images were used. It was found that apparently similar kaou images could be retrieved by the proposed method, improving the retrieval quality.
机译:介绍了作者小组开发的对kaou图像的基于内容的图像检索(CBIR)系统的改进。 Kaous是手写的字母组合,出现在日本的旧文件上,像汉字一样带有艺术装饰。 Kaous在历史文献的研究中起着重要作用,其中涉及浏览和比较大量样本。在这项工作中,介绍了一种用于CBIR的kaou图像建模的新方法,该方法除了常规使用的轮廓特征外,还合并了封闭kaou区域的阴影信息。查询和词典图像的不相似度被计算为组成区域的位置,轮廓形状和颜色的基本差异的加权总和。使用弛豫匹配和经验定义的距离函数对这些基本差异进行了评估。在实验中,使用了一组2455 kaou图像。结果发现,通过提出的方法可以检索到相似的kaou图像,从而提高了检索质量。

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