A Modified Approach for Face Recognition using PSO and ABC Optimization
P. Malin Bruntha1, S. Dhanasekar2, K. Martin Sagayam3, S. Immanuel Alex Pandian4
1P. Malin Bruntha, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore (Tamil Nadu), India.
2S. Dhanasekar, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore (Tamil Nadu), India.
3K. Martin Sagayam, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore (Tamil Nadu), India.
4S. Immanuel Alex Pandian, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore (Tamil Nadu), India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1571-1577 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6010058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Face Recognition (FR) has established noteworthy attention in the recent years due to its wide applications in various fields. FR technology uses image processing algorithms for comparing and verifying the human faces. This paper proposes a FR system which employs a novel mixture of Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Swarm Intelligence (SI). FFT and DCT help in extracting the features efficiently. PSO and ABC are used for feature selection that finds the best solution for a given problem. Many hybrid approaches are used to overcome its weakness and more over fit for various applications. The usage of transformation techniques helps in reducing image information redundancy. Experimental results show that there is a notable reduction in the number of features and a considerable increase in the recognition rate.
Keyword: ABC, DCT, FFT, PSO, Swarm Intelligence
Scope of the Article: Discrete Optimization.