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Comparative analysis of color and texture features in content based image retrieval

机译:基于内容的图像检索中颜色和纹理特征的比较分析

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Content-based image retrieval is a system which extracts the relevant set of images and matches with query image from large number of dataset. CBIR is used in many important areas such as education, defense, biomedical, crime prevention etc. In CBIR, the images are indexed according to content of image i.e. color, texture and shape that are derived from images. Many features and algorithms can be used to improve retrieval accuracy and to reduce the retrieval time. In this paper, we compare the different algorithms to extract color and texture features of an image and retrieve the relevant images. We measure the similarity between two images using different distance measures. The performance of each method has been individually evaluated in terms of average precision.
机译:基于内容的图像检索是一种提取相关图像集并与大量数据集中的查询图像进行匹配的系统。 CBIR用于许多重要领域,例如教育,国防,生物医学,犯罪预防等。在CBIR中,图像是根据图像内容(即从图像派生的颜色,纹理和形状)进行索引的。许多功能和算法可用于提高检索精度并减少检索时间。在本文中,我们比较了不同的算法以提取图像的颜色和纹理特征并检索相关图像。我们使用不同的距离度量来测量两个图像之间的相似度。每种方法的性能均根据平均精度进行了单独评估。

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