Abstract
Polygonal approximation (PA) is a challenging problem in representation of images in computer vision, pattern recognition and image analysis. This paper proposes a stochastic technique-based firefly algorithm (FA) for PA. This technique customizes a kind of randomization by searching a set of solutions. In contrast, PA requires more combination of approximation to find an optimal solution. The algorithm involves several steps to produce better results. The attractiveness and brightness of the firefly have been used efficiently to solve the approximation problem. While compared to other similar algorithms, FA is independent of velocities which are considered as an advantage for this algorithm. Subsequently, the multi-swarm nature of FA allows finding multiple optimal solutions concurrently. This technique achieves the main goal of PA that is minimum error value with less number of dominant points. The experimental results show that proposed algorithm generates better solutions compared to other algorithms.
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Venkateswara Reddy, L., Davanam, G., Pavan Kumar, T., Sunil Kumar, M., Narendar, M. (2023). Bio-Inspired Firefly Algorithm for Polygonal Approximation on Various Shapes. In: Rao, B.N.K., Balasubramanian, R., Wang, SJ., Nayak, R. (eds) Intelligent Computing and Applications. Smart Innovation, Systems and Technologies, vol 315. Springer, Singapore. https://doi.org/10.1007/978-981-19-4162-7_10
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DOI: https://doi.org/10.1007/978-981-19-4162-7_10
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