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Content based Image Retrieval and Classification using Support Vector Machine
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 92 - Number 7 |
| Year of Publication: 2014 |
| Authors: Spurti Shinde, Ashwini Lendal, Nikita Bajaj, Yogita Shelar |
10.5120/16019-4979
|
Spurti Shinde, Ashwini Lendal, Nikita Bajaj, Yogita Shelar . Content based Image Retrieval and Classification using Support Vector Machine. International Journal of Computer Applications. 92, 7 ( April 2014), 8-12. DOI=10.5120/16019-4979
Abstract
Content Based Image Retrieval (CBIR) is a traditional and developing trend in Digital Image Processing. Therefore the use of CBIR to search and retrieve the query image from wide range of database is increasing. In this paper we are going to explore an efficient image retrieval technique which uses local color, shape and texture features. So, efficient image retrieval algorithms based on RGB histograms, Geometric moment and Co-occurrence Model is proposed for color, shape and texture respectively. Results based on this approach are found encouraging in terms of color, shape and texture image classification accuracy. After the features are selected, an SVM classifier is trained to distinguish between relevant and irrelevant images accordingly.
References
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