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Reseach Article

Enhanced Semantic Image Retrieval using Feature Extraction and KNN Techniques

by Nitesh Rastogi, Deepak Chaudhary
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 13
Year of Publication: 2016
Authors: Nitesh Rastogi, Deepak Chaudhary
10.5120/ijca2016908582

Nitesh Rastogi, Deepak Chaudhary . Enhanced Semantic Image Retrieval using Feature Extraction and KNN Techniques. International Journal of Computer Applications. 136, 13 ( February 2016), 23-28. DOI=10.5120/ijca2016908582

@article{ 10.5120/ijca2016908582,
author = { Nitesh Rastogi, Deepak Chaudhary },
title = { Enhanced Semantic Image Retrieval using Feature Extraction and KNN Techniques },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 13 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 23-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number13/24215-2016908582/ },
doi = { 10.5120/ijca2016908582 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:37:00.995626+05:30
%A Nitesh Rastogi
%A Deepak Chaudhary
%T Enhanced Semantic Image Retrieval using Feature Extraction and KNN Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 13
%P 23-28
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In addition of that, the technique required some additional techniques to correct the retrieval process such as user feedback, these methods consumes additional time of search. Thus a new technique with hybrid concept is proposed for improving the content based image search. The proposed technique includes the technique to train the system using the image features and text for annotation of image. For identifying the images more accurately the text and image features are used. Finally to retrieve the data (image) using user query (image or text) a KNN algorithm is implemented with it. The implementation of the proposed model is performed using visual studio technology and their performance in terms of time and space complexity is estimated. In addition of that the performance in terms of accuracy and error rate is also provided for demonstrating the relevancy of image search.

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Index Terms

Computer Science
Information Sciences

Keywords

CBSIR Image Retrieval Tag based feature computation system modeling KNN LBP.