A Competitive Parallel Animated Oat Optimization Algorithm for Reversible Digital Watermarking^#

Shu-Chuan Chu^1,2, Libin Fu², Jeng-Shyang Pan^1,2,3,*
1 School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China
2 College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China
3 Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan
* Corresponding Author: Jeng-Shyang Pan. Email: email
# Presented at the International Conference on Machine Intelligence Theory and Applications 2026; 2026 Feb 24–28; Dunedin, New Zealand
(This article belongs to the Special Issue: Advances in Computational Intelligence for Complex Systems)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2026.084391

Received 21 April 2026; Accepted 29 June 2026; Published online 16 July 2026

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Abstract

The Animated Oat Optimization Algorithm (AOO) is a novel evolutionary algorithm inspired by the behavior of animated oats. This paper proposes a Competitive Parallel Animated Oat Optimization Algorithm (CPAOO) comprising two components. First, a parallel strategy is employed in which inter-subpopulation communication is triggered at predefined iteration thresholds to balance exploration and exploitation. Second, a grouped competition strategy with incentive mechanisms is introduced, enabling the prioritized evolution of superior individuals to enhance the algorithm’s efficiency. Furthermore, building on the Prediction Error Expansion (PEE) algorithm, this paper proposes a Dual-Layer PEE (DLPEE) algorithm for reversible digital watermarking. Based on differences in pixel values around embedding points, image blocks are classified as either smooth or textured regions. The CPAOO algorithm is used to optimize the weights of the pixel predictor and to prioritize embedding secret information in smooth blocks. This approach enhances both the embedding capacity and the invisibility of the watermarked data. Experimental results demonstrate that the proposed methods achieve satisfactory performance.