A novel visual tracking method using stochastic fractal search algorithm

Charef-Khodja, Djemai; Toumi, Abida; Medouakh, Saadia; Sbaa, Salim

doi:10.1007/s11760-020-01748-7

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…The results were compared with six other algorithms, showing an excellent ability to solve this problem. In [42], stochastic fractal search was proposed as a solution to the problem of visual tracking. The algorithm exhibited satisfactory results in difficult instances of this problem in comparison with other state-of-the-art algorithms.…”

Section: State Of the Artmentioning

confidence: 99%

Stochastic Fractal Search Algorithm Improved with Opposition-Based Learning for Solving the Substitution Box Design Problem

2022

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The main component of a cryptographic system that allows us to ensure its strength against attacks, is the substitution box. The strength of this component can be validated by various metrics, one of them being the nonlinearity. To this end, it is essential to develop a design for substitution boxes that allows us to guarantee compliance with this metric. In this work, we implemented a hybrid between the stochastic fractal search algorithm in conjunction with opposition-based learning. This design is supported by sequential model algorithm configuration for the proper parameters configuration. We obtained substitution boxes of high nonlinearity in comparison with other works based on metaheuristics and chaotic schemes. The proposed substitution box is evaluated using bijectivity, the strict avalanche criterion, nonlinearity, linear probability, differential probability and bit-independence criterion, which demonstrate the excellent performance of the proposed approach.

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Section: State Of the Artmentioning

confidence: 99%

Stochastic Fractal Search Algorithm Improved with Opposition-Based Learning for Solving the Substitution Box Design Problem

2022

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“…The fitness function value ) ( j X fitness of image region j in the target tracking optimization problem in this study is defined as the similarity function value between image block Xj and real target region Xc (the optimal solution found in the last frame). The Bhattacharyya function ) ( j X  is used to determine the similarity between different image blocks [32].…”

Section: Fitness Functionmentioning

confidence: 99%

Robust Visual Tracking Based on a Modified Flower Pollination Algorithm

Xiao

Yang

2021

IEEE Access

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“…This paper is an introduction to the algorithms presented in Salimi [9], namely, fractal search ([9] section 3) and stochastic fractal search ([9] section 4). Also mentioning applications in engineering and science using stochastic fractal search as an optimisation framework, Optimizing PID controller parameters for an automatic folder regulator [2], Another application [1] which used SFS as a localization backend for a visual tracking algorithm.…”

Section: Related Workmentioning

confidence: 99%

A Survey On (Stochastic Fractal Search) Algorithm

ElKomy

2021

Preprint

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Evolutionary Algorithms are naturally inspired approximation optimisation algorithms that usually interfere with science problems when common mathematical methods are unable to provide a good solution or finding the exact solution requires an unreasonable amount of time using traditional exhaustive search algorithms. The success of these population-based frameworks is mainly due to their flexibility and ease of adaptation to the most different and complex optimisation problems. This paper presents a metaheuristic algorithm called Stochastic Fractal Search, inspired by the natural phenomenon of growth based on a mathematical concept called the fractal, which is shown to be able to explore the search space more efficiently. This paper also focuses on the algorithm steps and some example applications of engineering design optimisation problems commonly used in the literature being applied to the proposed algorithm.

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A novel visual tracking method using stochastic fractal search algorithm

Cited by 7 publications

References 15 publications

Stochastic Fractal Search Algorithm Improved with Opposition-Based Learning for Solving the Substitution Box Design Problem

Stochastic Fractal Search Algorithm Improved with Opposition-Based Learning for Solving the Substitution Box Design Problem

Robust Visual Tracking Based on a Modified Flower Pollination Algorithm

A Survey On (Stochastic Fractal Search) Algorithm

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