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New Approach for Content based Image Retrieval System using Texture and Color Features
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 26 |
| Year of Publication: 2018 |
| Authors: Alka Choudhary, Assistant Professor |
10.5120/ijca2018916553
|
Alka Choudhary, Assistant Professor . New Approach for Content based Image Retrieval System using Texture and Color Features. International Journal of Computer Applications. 179, 26 ( Mar 2018), 22-25. DOI=10.5120/ijca2018916553
Abstract
Now-a-days Content based Image Retrieval (CBIR) techniques are in great demand in every field. In this paper a new approach is proposed for retrieving images. Color Features is extracted from HSV image using color histogram. The texture feature gets extracted from the RGB image by applying GLDM technique. Feature vectors of query image and database image are compared using similarity measures. After comparisons distance vectors are added to get a resultant vector. The images are ranked according to the resultant vector and retrieved. This approach is implemented using MATLAB8.0. The results and conclusions are shown in the paper.
References
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- Stian Edvardsen.,” Classification of Images using Color, CBIR Distance Measures and Genetic Programming”, An evolutionary Experiment, Norwegian University of Science and Technology Department of Computer and Information Science ,2006.
- Amandeep Khokher, Rajneesh Talwar,” Content based Image retrieval: Feature Extraction Techniques and Applications, International Conference on Recent Advances and Future Trends in the Information Technology, IJCA,2012.
- Rafael Gonzalez. Richard E. Woods, Steven L. Eddins,” Fundamentals of digital Image processing”, 2006.
- Wikipedia, the free encyclopedia/texture/texels.
- Krishna Kumar Pandey1& Nishchol Mishra, “design & development of color matching algorithm for image retrieval using histogram and segmentation techniques”, International Journal of Information Technology and Knowledge Management Volume 4, No. 2, July-December 2011.
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