Abstract
Ant colony optimization (ACO) is a cooperative search algorithm inspired by the behavior of real ants in nature. In this work, ACO is applied to solve the problem of extracting inserted data without recourse to the original image. Indeed, the heaviness of the extraction procedure of the watermark with the conventional watermarking methods has motivated the search for a new algorithm. The basic idea of the ACO approach is to use the pheromone trails as a medium for indirect communication to guide ants to the food source. This mechanism is used in this article, the ants are guided by the variation in pixel intensity values and their movement establishes a pheromone matrix that represents the hidden information. Our experimental results show the feasibility and success of the proposed method.
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