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An Effective Approach to an Image Retrieval using SVM Classifier

Mohd. Aquib Ansari1 , Diksha Kurchaniya2 , Manish Dixit3 , Punit Kumar Johari4

  1. Dept. of CSE/IT, Madhav Institute of Technology and Science, Gwalior, India.
  2. Dept. of CSE/IT, Madhav Institute of Technology and Science, Gwalior, India.
  3. Dept. of CSE/IT, Madhav Institute of Technology and Science, Gwalior, India.
  4. Dept. of CSE/IT, Madhav Institute of Technology and Science, Gwalior, India.

Correspondence should be addressed to: aaquib.mits@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-6 , Page no. 62-72, Jun-2017

Online published on Jun 30, 2017

Copyright © Mohd. Aquib Ansari, Diksha Kurchaniya, Manish Dixit, Punit Kumar Johari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Mohd. Aquib Ansari, Diksha Kurchaniya, Manish Dixit, Punit Kumar Johari, “An Effective Approach to an Image Retrieval using SVM Classifier,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.62-72, 2017.

MLA Style Citation: Mohd. Aquib Ansari, Diksha Kurchaniya, Manish Dixit, Punit Kumar Johari "An Effective Approach to an Image Retrieval using SVM Classifier." International Journal of Computer Sciences and Engineering 5.6 (2017): 62-72.

APA Style Citation: Mohd. Aquib Ansari, Diksha Kurchaniya, Manish Dixit, Punit Kumar Johari, (2017). An Effective Approach to an Image Retrieval using SVM Classifier. International Journal of Computer Sciences and Engineering, 5(6), 62-72.

BibTex Style Citation:
@article{Ansari_2017,
author = {Mohd. Aquib Ansari, Diksha Kurchaniya, Manish Dixit, Punit Kumar Johari},
title = {An Effective Approach to an Image Retrieval using SVM Classifier},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2017},
volume = {5},
Issue = {6},
month = {6},
year = {2017},
issn = {2347-2693},
pages = {62-72},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1304},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1304
TI - An Effective Approach to an Image Retrieval using SVM Classifier
T2 - International Journal of Computer Sciences and Engineering
AU - Mohd. Aquib Ansari, Diksha Kurchaniya, Manish Dixit, Punit Kumar Johari
PY - 2017
DA - 2017/06/30
PB - IJCSE, Indore, INDIA
SP - 62-72
IS - 6
VL - 5
SN - 2347-2693
ER -

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Abstract

Content Based Image Retrieval (CBIR) is an important and challenging research area of digital image processing for browsing and retrieving the images from the wide range of image database. The basic requirement of the CBIR system is to retrieve the relevant information from large image database following to query image with higher system performance. In this paper the two step strategy is developed in which the first step is to extract the low level or pixel level features of the image by using color, texture and shape descriptor. Here an efficient fused feature extraction method based on color and edge directivity descriptor (CEDD) for extracting the color as well as texture features and two level discrete wavelet transform (2D-DWT) for extracting the shape feature of the image is proposed. While, in the second step the SVM classifier is used to classify the images into different classes and to handle irrelevant examples. For retrieving the similar images following to query image the Euclidean distance similarity measurement is used. This fused and classified based proposed scheme applied on different image databases and proved that it is providing better results over various existing methods and individual approaches.

Key-Words / Index Term

CBIR, feature extraction, color and edge directive descriptor, 2 level discrete wavelet transform, support vector machine, similarity measurement

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