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Content-based image retrieval using moment-preserving edge detection

机译:使用保矩边缘检测的基于内容的图像检索

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摘要

A content-based image retrieval algorithm based on a new edge detection technique is proposed. Both the query and database images are divided into non-overlapping square blocks and coded by the mean in each uniform block and by edge information in each non-uniform block. The coded blocks of a query image are then used to find matches from an image database. The edge feature in a given block is detected by applying the moment-preserving principle to the image data. The edge directions are approximated by multiples of 45° to speed up the matching process without introducing obvious distortion. For a larger database, a selective filtering strategy based on the visual-pattern histograms is also described to further speed up the retrieval process. The solution to the edge detection problem in a given block is also analytic. This algorithm can be performed very fast for large database applications with no need for special hardware.
机译:提出了一种基于新型边缘检测技术的基于内容的图像检索算法。查询图像和数据库图像都被划分为非重叠的正方形块,并通过每个均匀块中的均值和每个非均匀块中的边缘信息进行编码。然后,将查询图像的编码块用于从图像数据库中查找匹配项。给定块中的边缘特征是通过将矩保持原理应用于图像数据来检测的。边缘方向近似为45°的倍数,以加快匹配过程,而不会引入明显的失真。对于更大的数据库,还描述了基于视觉模式直方图的选择性过滤策略,以进一步加快检索过程。给定块中边缘检测问题的解决方案也是解析性的。对于大型数据库应用程序,无需特殊硬件即可非常快速地执行此算法。

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