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Two Tier Approach for Automatic Retrieval of MRI Brain Image by Feature Extraction
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 132 - Number 14 |
| Year of Publication: 2015 |
| Authors: Gayatri Chavan, Sonal Gore |
10.5120/ijca2015907661
|
Gayatri Chavan, Sonal Gore . Two Tier Approach for Automatic Retrieval of MRI Brain Image by Feature Extraction. International Journal of Computer Applications. 132, 14 ( December 2015), 46-48. DOI=10.5120/ijca2015907661
Abstract
Content Based Image Retrieval(CBIR) is also known as Query By Image Content(QBIC) is the one of the application of computer vision techniques, which retrieves the images from the image database instead of text. The CBIR is gaining the popularity in medical domain, because CBIR techniques help to search the digital images in the large database. The proper feature extraction and matching process, retrieves stored image from database by supplying the query image. The features such as color, shape texture or combination of them. In this paper, focused on texture and shape feature for extracting the image from database, by introducing the SVM (support vector machine) classifier followed by KNN (K-nearest neighbor). In this paper propose a efficient retrieval of image using a supervised classifier which focused on the texture features. Segmentation based Fractal Texture Analysis or SFTA algorithm is used to extract the texture feature from images. To select best features from extracted features to train the classifier, achieve better feature optimization. The classification is done on the database and it is classified in to three categories such as normal, benign and malignant. The query image is classified using a classifier and retrieve the relevant image from the database from a particular class.
References
- Guoyong Duan, Jing Yang, Yilong Yang , “Content based image retrieval research” ,2011 International conferances on physics science and technology(ICPST 2011)
- Priyanka P. Buch,Madhuri V. Vaghasia, Sahista M. Machchhar,”Comparative analysis of content based image retrieval using both color and texture”, Institute of technology, Nirma univercity, Ahemedabad-382 481, December,2011.
- Keatn Machhale, Hari babu nandpur, Vivek kapur, Laxmi Kostan, “MRI brain cancer classification using hybrid classifier(SVM-KNN),” 2015 International conference on industrial instrumentation and control(ICIC),May-2015.
- R. Usha, K. Perumal,”Content based image retrieval using combined features of color and texture features with SVM classification”,International journal of computer science and communication networks,Vol 4(5), 169-174.\
- Mohanapriya.S, Vadivel.M,” Automatic retrieval of MRI brain image using multiqueries system”, IEEE,2014
- Alceu Ferraz Costa, Gabriel Humpire-Mamani, Agma Juci Machado Traina’” An Efficient Algorithm for Fractal Analysis of Textures”, 2012 XXV SIBGRAPI Conference on Graphics, Patterns and Images
- H. Muller, N. Michoux, D. Bandon, and A. Geissbuhler, “A review of content-based image retrieval systems in medical applications clinical benefits and future directions,” Int. J. Med. Informat., vol. 73, no.1pp. 1–23, 2004.
- H.B.Kekre, Tanuja K. Sarode, Sudeep D. Thepade, Vaishali Suryavanshi,”Improved texture feature based image trtrieval using Kekre,s fast codebook generation algorithm”,August 2011.
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