Retrieval of Images Using SVM
DOI:
https://doi.org/10.53555/nncse.v2i3.500Keywords:
SVM, dataset, image classification, image retrieval, CBIR, feature matchingAbstract
Image retrieval is a technique which is used to search and retrieve images from a large database of digital images. Content-based image retrieval (CBIR) is a technique which allows searching images from large scale image database based on contents as needed by user.This paper introduces a technique to retrieve images by classifying it on the basis of the features and characteristics it contains using Support Vector Machine (SVM). The dataset of images is created which is used for feature matching purpose by SVM to find similar images from the database and based on user requirements images are retrieved.
References
Sumiti Bansal, Er. Rishamjot Kaur, “A Review on Content Based Image Retrieval using SVM”, International Journal of Advanced Research in
Computer Science and Software Engineering , Volume 4, Issue 7, July 2014
Neera Lal, Neetesh Gupta, Amit Sinhal , “A Review of Image Classification Techniques in Content Based Image Retrieval”, Neera Lal et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (5) , 2012
N. Kumaran, Dr. R. Bhavani, “ Texture and Shape Content Based MRI Image Retrieval System”, International Journal of Innovative Research in Science, Engineering and Technology, Volume 3, Special Issue 1, February 2014
R.Ravinder Reddy, B.Kavya, Y Ramadevi, Ph.D., “A Survey on SVM Classifiers for Intrusion Detection”, International Journal of Computer Applications (0975– 8887) ,Volume 98– No.19, July 2014
Amanbir Sandhu, Aarti Kochhar, “Content Based Image Retrieval using Texture, Color and Shape for Image Analysis”, International Journal of Computers & Technology Volume 3, No. 1, AUG, 2012
S. Mangijao Singh , K. Hemachandran, “Content Based Image Retrieval using Color Moment and Gabor based images using color movement and Gabor Based Image Retrieval using Color Moment and Gabor Texture Feature texture”, Department of Computer Science, Assam University, Silchar, Assam, India, Vol. 9, Issue 5, No 1, September 2012
Reshma Chauudhari and A.M Patil “Content Based Image Retrieval Using Color and Shape Features”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol.1, 2012
P.S. Malge et.al “Performance Evaluation of Texture based Image Retrieval”, International Journal of Computer Applications (0975 – 8887) Volume 72– No.2, May 2013
Ramadass Sudhir et. Al, “A Efficient Content based Image Retrieval System using GMM and Relevance Feedback”, International Journal of Computer Applications (0975 – 8887) Volume72– No.22, June 2013
A. Padma Nanthagopal, R. Sukanesh, “Wavelet statistical texture features-based segmentation and classification of brain computed tomography images”, IET Image Processing 2012
Aditi Mehta, “Review and Comparison of Various Feature Extraction Techniques in CBIR”, International Journal of Computer Applications (0975 – 8887) Volume 71– No.23, June 2013
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.