Adaptive Waterwheel Plant Optimization for Enhanced Region Selection in Robust Video Watermarking
Khushboo Chhikara, Manoj Kumar · IETE Journal of Research · 2025
In the digital age, ensuring data security amidst the widespread use of communication devices like smartphones and computers poses significant challenges. Video watermarking serves as a crucial technique for safeguarding data during transmission, involving intricate processes of embedding and extraction. However, the effectiveness of many existing methods in selecting optimal pixels for embedding remains limited, impacting both quality and robustness. This paper introduces a novel video watermarking approach designed to address these challenges. The proposed technique begins by extracting key frames from a cover video using Structural Similarity Index Measurement (SSIM) and employs an adaptive waterwheel plant optimization (AWaPO) algorithm to select optimal embedding regions. To enhance security, the selected regions undergo 2 level-discrete wavelet transform (2L-DWT), with the LL band chosen for embedding secret data encrypted using the enhanced blowfish algorithm (EnBf). Experimental results demonstrate the efficacy of the approach, showcasing its ability to achieve high security, robustness, and quality preservation in watermarking applications.