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Image retrieval based on color distribution entropy

机译:基于颜色分布熵的图像检索

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摘要

Color histogram is an important technique for color image database indexing and retrieving. However, the main problem with color histogram indexing is that it does not take the color spatial distribution into consideration. Previous researches have proved that the effectiveness of image retrieval increases when spatial feature of colors is included in image retrieval. In this paper, two new descriptors, color distribution entropy (CDE) and improved CDE (I-CDE), which introduce entropy to describe the spatial information of colors, are presented. In comparison with the spatial chromatic histogram (SCH) and geostat which also measure the global spatial relationship of colors, the experiment results show that CDE and I-CDE give better performance than SCH and geostat.
机译:颜色直方图是用于彩色图像数据库索引和检索的一项重要技术。但是,颜色直方图索引编制的主要问题是它没有考虑颜色空间分布。先前的研究已经证明,当图像检索中包含颜色的空间特征时,图像检索的有效性会提高。本文提出了两个新的描述符,即颜色分布熵(CDE)和改进的CDE(I-CDE),它们引入了熵来描述颜色的空间信息。与也测量颜色的整体空间关系的空间色度直方图(SCH)和geostat相比,实验结果表明CDE和I-CDE比SCH和geostat具有更好的性能。

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