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Review of CBIR Related with Low Level and High Level Features

机译：与低水平和高水平功能相关的CBIR回顾

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摘要

The method of retrieving pictures from the massive image info is termed as content based mostly image retrieval (CBIR). CBIR is that the standard analysis space of interest. CBIR paves the approach of user interaction with giant info by satisfying their queries within the sort of pictures. This paper discusses the recital of a CBIR system that is in and of itself repressed by the options adopted to symbolize the pictures within the record and conjointly study the approaches of a spread of ways that deals with the extraction of options supported low and high level options of images with the query image provided. The most contribution of this work could be a comprehensive comparison between the low level and high level feature approaches to CBIR.To retrieve the pictures in a good manner this paper provides associate platform for victimization the ways which can able to specialize in each low level and high level options and created clarification regarding high level options will retrieve images a lot of relevant to the query image provided.
机译：从海量图像信息中检索图片的方法称为基于内容的内容，主要是图像检索（CBIR）。 CBIR是感兴趣的标准分析空间。 CBIR通过在图片中满足他们的查询，为用户与巨量信息进行交互铺平了道路。本文讨论了一个CBIR系统的独奏会，它本身会被用来在记录中象征图片的选项所压制，并联合研究了多种方法的处理方法，这些方法用于处理支持低级和高级选项的选项的提取。提供查询图像的图像集。这项工作的最大贡献是可以对CBIR的低层和高层特征方法进行全面比较。为了以良好的方式检索图片，本文提供了一种受害平台，可以专门研究每个低层和低层的图像。高级选项并创建有关高级选项的说明，将检索与提供的查询图像很多相关的图像。

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