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Color uniformity descriptor: An efficient contextual color representation for image indexing and retrieval

机译：颜色均匀性描述符：用于图像索引和检索的高效上下文颜色表示

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摘要

Color is a rich source of visual information for the effective characterization of image content. The recognition of texture or shape elements in images is strongly associated with the analysis of the image color layout. This paper presents a contextual color descriptor designed especially to be applied to CBIR tasks in heterogeneous image databases. The proposed color uniformity descriptor (CUD) clusters perceptually similar image color regions according to the uniformity analysis of their neighbor pixels. CUD produces vast color image details with a thin histogram, whilst preserving the balance between uniqueness and robustness. CUD is computationally efficient and can achieve high precision and throughput rates when used in CBIR. Experimental results show that CUD performs comparably against local features and multiple features state-of-the-art approaches that require more complex data manipulation. Results demonstrate that CUD provides strong image discrimination even in the presence of significant content variation.
机译：颜色是有效表征图像内容的丰富视觉信息来源。图像中纹理或形状元素的识别与图像颜色布局的分析紧密相关。本文提出了一种上下文颜色描述符，该描述符专门设计用于异构图像数据库中的CBIR任务。提出的颜色均匀性描述符（CUD）根据对它们相邻像素的均匀性分析，在感知上相似的图像颜色区域之间进行聚类。 CUD生成的彩色图像细节具有很细的直方图，同时保留了唯一性和鲁棒性之间的平衡。当在CBIR中使用时，CUD的计算效率很高，并且可以实现高精度和高吞吐率。实验结果表明，CUD的性能与本地功能和需要更复杂数据处理的多种功能的最新技术相当。结果表明，即使存在明显的内容差异，CUD仍可提供强大的图像辨别力。

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