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首页> 外文会议>Iranian Conference on Signal Processing and Intelligent Systems >Content-based Image Retrieval Using Color Difference Histogram in Image Textures
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Content-based Image Retrieval Using Color Difference Histogram in Image Textures

机译：在图像纹理中使用色差直方图的基于内容的图像检索

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摘要

The aim of content-based image retrieval system is finding similar images to the query image from a database based on its visual content. In this paper, a novel retrieval system based on human vision is proposed. A factor that has a high impact on the search process is a set of features which are used in. The recent studies emerged that the human eye system considers the image content, texture, and color properties more than other features. Therefore, to retrieve more precisely the images, features should be used that are close to the human eye system. In the current paper, at first, the texture is extracted from the images using the local binary patterns algorithm. After that, the color differences of two adjacent pixels with the same texture are calculated in the HSV color space. Afterward, the histogram is taken from the color difference values. The obtained features from the histogram can describe the visual content of the images in more detail. Finally, the effective features are selected based on their entropy value. The prominent advantage of the proposed method is the lack of implementation of segmentation, clustering, training, and any other method of machine learning, which requires a lot of processing and time. The method is evaluated on two standard Corel 10K and Corel 5K databases, and its retrieval rate is significantly improved compared to some recent methods.
机译：基于内容的图像检索系统的目的是根据其可视内容从数据库中查找与查询图像相似的图像。本文提出了一种基于人类视觉的新型检索系统。对搜索过程影响最大的因素是所使用的一组功能。最近的研究表明，人眼系统比其他功能更重视图像内容，纹理和颜色属性。因此，为了更精确地检索图像，应使用接近人眼系统的特征。在当前的论文中，首先，使用局部二进制模式算法从图像中提取纹理。之后，在HSV颜色空间中计算具有相同纹理的两个相邻像素的色差。然后，从色差值中提取直方图。从直方图获得的特征可以更详细地描述图像的视觉内容。最后，根据有效特征的熵值选择有效特征。所提出的方法的突出优点是缺乏分割，聚类，训练和任何其他机器学习方法的实现，这需要大量的处理和时间。该方法在两个标准Corel 10K和Corel 5K数据库上进行了评估，与某些最新方法相比，其检索率得到了显着提高。

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