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Image retrieval systems based on compact shape descriptor and relevance feedback information

机译:基于紧凑形状描述符和相关反馈信息的图像检索系统

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摘要

One of the most important and most used low-level image feature is the shape employed in a variety of systems such as document image retrieval through word spotting. In this paper an MPEG-like descriptor is proposed that contains conventional contour and region shape features with a wide applicability from any arbitrary shape to document retrieval through word spotting. Its size and storage requirements are kept to minimum without limiting its discriminating ability. In addition to that, a relevance feedback technique based on Support Vector Machines is provided that employs the proposed descriptor with the purpose to measure how well it performs with it. In order to evaluate the proposed descriptor it is compared against different descriptors at the MPEG-7 CE1 Set B database.
机译:最重要和最常用的低级图像功能之一是在各种系统中采用的形状,例如通过单词斑点检索文档图像。在本文中,提出了一种类似MPEG的描述符,该描述符包含常规的轮廓和区域形状特征,从任意形状到通过单词斑点检索文档都具有广泛的适用性。在不限制其区分能力的情况下,将其大小和存储要求保持在最低水平。除此之外,还提供了一种基于支持向量机的相关性反馈技术,该技术采用了所提出的描述符,目的是测量其执行效果。为了评估建议的描述符,将其与MPEG-7 CE1 Set B数据库中的不同描述符进行比较。

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