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A Review on Content based Image Retrieval
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 132 - Number 13 |
| Year of Publication: 2015 |
| Authors: Tanvi Patel, Mayank Kapadia, Jemish Maisuria |
10.5120/ijca2015907584
|
Tanvi Patel, Mayank Kapadia, Jemish Maisuria . A Review on Content based Image Retrieval. International Journal of Computer Applications. 132, 13 ( December 2015), 22-25. DOI=10.5120/ijca2015907584
Abstract
Literature survey is an important for understanding and gaining much more knowledge about the specific area of a subject. An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. Content-based image retrieval (CBIR) is an image search technique that complements the traditional text-based retrieval of images by using visual features, such as color, texture, and shape. This system retrieve according to the query image; that is, the user provides or selects a query image and chooses a distance measure that will be used to compare the query image to the images stored in the database. This paper is attempt to explore different CBIR technique and their application.
References
- Yogita Mistry 1, Dr.D.T. Ingole, ‘Survey on Content Based Image Retrieval Systems’, IJIRCCE International Journal of Innovative Research in Computer and Communication Engineering, Vol. 1, October 2013.
- Peiqiang Zhang, Hongguang Zhu, ‘Medical Image Retrieval Based on Co-Occurrence Martix and Edge Histogram’, IEEE 2010.
- S. Arivazhagan, L. Ganesan b, ‘Texture Segmentation Using Wavelet Transform’, Pattern Recognition Letters 24 (2003) 3197–3203.
- Hassan Farsi, Sajad Mohamadzadeh, ‘Colour And Texture Feature-based Image Retrieval By Using Hadamard Matrix In Discrete Wavelet Transform’, IET Image Process., 2013, Vol. 7, Iss. 3, pp. 212–218.
- James Z. Wang, Jia Li, and Gio Wiederhold, ‘SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries’, IEEE Transactions On Pattern Analysis And Machine Intelligence, VOL. 23, NO. 9, September 2001.
- Haoyu Ren, Ze-Nian Li, ‘Object Detection Using Edge Histogram Of Oriented Gradient’, IEEE 2014.
- A. Gebejes, R. Huertas, ‘Texture Characterization based on Grey-Level Co-occurrence Matrix’, Conference of Informatics and Management Sciences March, 25. - 29. 2013.
- A.Srinagesh, K.Aravinda, G.P.Saradhi Varma, A.Govardhan, M. SreeLatha , ‘A Modified Shape Feature Extraction Technique For Image Retrieval’, International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378, Volume-1, Issue-8, June 2013.
- Jun Yue, Zhenbo Li, Lu Liu and Zetian Fu, “Content Based Image Retrieval Using Color And Texture Fused Features”, ELSEVIER ,pg.no. 1121-1127,2011.
- Suman Lata and Parul Preet Singh, ‘A Review on Content Based Image Retrieval System’, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), ISSN: 2277 128X, Volume 4, Issue 5, May 2014.
- Amanbir Sandhu and Aarti Kochhar , ‘Content Based Image Retrieval Using Texture, Color And Shape For Image Analysis’, International Journal of Computers & Technology (IJCT),Volume 3, No. 1, AUG, 2012.
- Shankar M. Patil, ‘Content Based Image Retrieval Using Color, Texture & Shape’, International Journal of Computer Science & Engineering Technology (IJCSET), ISSN: 2229-3345, Vol. 3 No. 9 Sep 2012.
- P. Mohanaiah, P. Sathyanarayana, L. GuruKumar, ‘Image Texture Feature Extraction Using GLCM Approach’, International Journal of Scientific and Research Publications, Volume 3, Issue 5, May 2013 1 ISSN 2250-3153.
- Ms. K. Arthi and Mr. J. Vijayaraghavan , ‘Content Based Image Retrieval Algorithm Using Colour Models’, International Journal of Advanced Research in Computer and Communication Engineering ((IJARCCE ), Vol. 2, Issue 3, March 2013.
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