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A Secure and Effective Image Retrieval Based on Robust Features

A Secure and Effective Image Retrieval Based on Robust Features
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Author(s): Swapna B. (Dr. M. G. R. Educational and Research Institute, India), Arulmozhi P. (Karpagam College of Engineering, India), Kamalahasan M. (Dr. M. G. R. Educational and Research Institute, India), Anuradha V. (Dr. M. G. R. Educational and Research Institute, India), Meenaakumari M. (Dr. M. G. R. Educational and Research Institute, India), Hemasundari H. (Dr. M. G. R. Educational and Research Institute, India) and Aathilakshmi T. (Dr. M. G. R. Educational and Research Institute, India)
Copyright: 2022
Pages: 21
Source title: Handbook of Research on Technologies and Systems for E-Collaboration During Global Crises
Source Author(s)/Editor(s): Jingyuan Zhao (University of Toronto, Canada) and V. Vinoth Kumar (Jain University, India)
DOI: 10.4018/978-1-7998-9640-1.ch005

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Abstract

The most typical approaches are content-based image retrieval systems. Content-based picture retrieval may be the only one in all the image retrieval techniques that uses user visual options of an image like color, form, and texture. The objective is to retrieve the set of pictures quickly and economically by supported color and texture options. Color is the foremost authoritative and utilized visual option that is invariant to image dimension and adjustment. Color car correlogram includes the special correlation and figures the mean color of all components of intensity about a distance k-th of a pixel of intensity the picture. Next, the feel feature may be a powerful region-based descriptor to provide a life of attributes like smoothness, coarseness, and regularity. Block distinction probabilities and block variation of native correlation features are analysed to speed up the retrieval method. BDIP may be a block-based approach to extract color and intensity features and live native brightness variation from the photographs.

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