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Review of CBIR Related with Low Level and High Level Features

Review of CBIR Related with Low Level and High Level Features
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Author(s): Tamil Kodi (Godavari Institute of Engineering and Technology (GIET), Rajahmundry, India & Saveetha University, Chennai, India), G. Rosline Nesa Kumari (Saveetha University, Chennai, India)and S. Maruthu Perumal (NBKR Inst. of Science and Technology,Nellore, India)
Copyright: 2016
Volume: 7
Issue: 1
Pages: 14
Source title: International Journal of Synthetic Emotions (IJSE)
DOI: 10.4018/IJSE.2016010103

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Abstract

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.

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