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Abstract
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Article Information:
Novel Approach to Content Based Image Retrieval Using Evolutionary Computing
Muhammad Imran, Rathiah Hashim and Noor Elaiza Abd Khalid
Corresponding Author: Muhammad Imran
Submitted: October 31, 2013
Accepted: January 24, 2014
Published: August 15, 2014 |
Abstract:
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Content Based Image Retrieval (CBIR) is an active research area in multimedia domain in this era of information technology. One of the challenges of CBIR is to bridge the gap between low level features and high level semantic. In this study we investigate the Particle Swarm Optimization (PSO), a stochastic algorithm and Genetic Algorithm (GA) for CBIR to overcome this drawback. We proposed a new CBIR system based on the PSO and GA coupled with Support Vector Machine (SVM). GA and PSO both are evolutionary algorithms and in this study are used to increase the number of relevant images. SVM is used to perform final classification. To check the performance of the proposed technique, rich experiments are performed using coral dataset. The proposed technique achieves higher accuracy compared to the previously introduced techniques (FEI, FIRM, simplicity, simple HIST and WH).
Key words: CBIR, evolutionary computing, genetic algorithm, PSO, SVM, ,
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Abstract
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Cite this Reference:
Muhammad Imran, Rathiah Hashim and Noor Elaiza Abd Khalid, . Novel Approach to Content Based Image Retrieval Using Evolutionary Computing. Research Journal of Applied Sciences, Engineering and Technology, (6): 691-701.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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