2022
DOI: 10.1016/j.jksuci.2019.03.009
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An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm

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Cited by 40 publications
(44 citation statements)
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“…Heuristic optimization algorithms offer solutions close to nonlinear mathematics and real life problems. In the literature, heuristic optimization algorithms have been applied in many different areas [83][84][85][86][87]. Particle Swarm Optimization (PSO), one of these algorithms, is a heuristic algorithm put forward by Kennedy and Eberhart in 1995 [88].…”
Section: Pso and Bpsomentioning
confidence: 99%
“…Heuristic optimization algorithms offer solutions close to nonlinear mathematics and real life problems. In the literature, heuristic optimization algorithms have been applied in many different areas [83][84][85][86][87]. Particle Swarm Optimization (PSO), one of these algorithms, is a heuristic algorithm put forward by Kennedy and Eberhart in 1995 [88].…”
Section: Pso and Bpsomentioning
confidence: 99%
“…This challenge can be dealt with by incorporating an evolutionary intelligence algorithm. The implementation is done by embedding a watermark in the DCT domain, accompanied by a nature-based optimization watermark [16]. This is due to the resistance to lossy JPEG compression [17].…”
Section: Dctmentioning
confidence: 99%
“…It is calculated through a mathematical ratio known as Peak Signal to Noise ratio (PSNR) as per Eqs. ( 15)- (16). The term robustness refers to the embedded watermark's ability to withstand image manipulation and geometric attacks.…”
Section: Quality Measuresmentioning
confidence: 99%
“…In order to improve the efficiency & effectiveness of an algorithm, the optimizations parameter plays a very important role. The algorithms designed for color image watermarking in the wavelet domain have been optimized by number of technique which include Singular Value Decomposition (SVD) [16], Support Vector Machine (SVM) [31,32], Ant Colony Optimization (ACO) [67], Independent Component Analysis (ICA), Fuzzy Logic [75], Genetic Algorithm (GA) [41], Firefly Algorithm (FA) [39], Modified Firefly Algorithm [56], Particle Swarm Optimization (PSO) [70], Artificial Bee Colony Algorithm [7], Differential Evolution (DE) [54], Cat Swarm Optimization (CSO) and Cuckoo Search (CS) [2]. The work based on the optimization techniques has been summarized as:…”
Section: Optimization Techniques Usedmentioning
confidence: 99%