دانلود مقاله ISI انگلیسی شماره 93192
ترجمه فارسی عنوان مقاله

کیفیت با کیفیت مطلوب بهینه سازی علامت گذاری به عنوان علامت گذاری به عنوان علامت گذاری شده با عصا مصنوعی

عنوان انگلیسی
A quality guaranteed robust image watermarking optimization with Artificial Bee Colony
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
93192 2017 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 72, 15 April 2017, Pages 317-326

ترجمه کلمات کلیدی
علامت قوی تصویری، فراماسونری، بهینه سازی، عملکرد تناسب اندام، کلنی زنبور عسل مصنوعی،
کلمات کلیدی انگلیسی
Robust image watermarking; Meta-heuristic; Optimization; Fitness function; Artificial Bee Colony;
پیش نمایش مقاله
پیش نمایش مقاله  کیفیت با کیفیت مطلوب بهینه سازی علامت گذاری به عنوان علامت گذاری به عنوان علامت گذاری شده با عصا مصنوعی

چکیده انگلیسی

Achieving robustness with a limited distortion level is a challenging design problem for watermarking systems in multimedia applications with a guaranteed quality requirement. In this paper, we provide an intelligent system for watermarking through incorporating a meta-heuristic technique along with an embedding method to achieve an optimized performance. The optimization objective is to provide the maximum possible robustness without exceeding a predetermined distortion limit. Hence, the quality level of the watermarking method could be guaranteed through that constraint optimization. A new fitness function is defined to provide the required convergence toward the optimum solution for the defined optimization problem. The fitness function is based on dividing its applied solution population into two groups, where each group is ranked according to a different objective. Thus, the multi-objectives in the problem are decoupled and solved through two single-objective sub-problems. Unlike existing watermarking optimization techniques, the proposed work does not require weighting factors. To illustrate the effectiveness of the proposed approach, we employ a recent watermarking technique, and then use it as the embedding method to be optimized. The Artificial Bee Colony is selected as the meta-heuristic optimization method in which the proposed fitness function is used. Experimental results show that the imposed quality constraint is satisfied, and that the proposed method provides enhanced robustness under different attacks for various quality thresholds. The presented approach offers a robust solution that can be applied to numerous multimedia applications such as film industry, intelligent surveillance and security systems.