Embedding of a digital watermark in a digital media is proving to be a workable solution for many of the recent problems like copyright protections and content authentication. However, the embedding of a digital watermark in a digital media is not without constraints. This requires perceptual shaping of a watermark in context of Human Visual System (HVS). The goal of this thesis is to develop a new watermarking scheme based on intelligent shaping of a digital watermark using GP. To achieve this goal, the research focuses on making efficient tradeoffs between two of the most important, but contradicting properties of a watermarking system; robustness and imperceptibility. This thesis makes the following contributions: (1) An analysis of the importance of perceptual shaping of a watermark in making a trade off between robustness and imperceptibility is performed, (2) intelligent search technique, like GP, is used to exploit the characteristics of HVS in evolving superior perceptual shaping functions, (3) the concept of bonus fitness has been proposed to implement multi-objective fitness function, in the GP simulation. This helps in simultaneously handling the estimated robustness and imperceptibility requirements during embedding stage, and actual robustness during decoding stage, (4) we realize that perceptual shaping of a watermark is not only important for making a superior trade off, but could also be used to tailor the watermark in accordance to an anticipated attack, (5) watermarking systems are becoming more and more sophisticated, as such this thesis, using intelligent search technique like GP, points towards the solution strategy of many complex issues in watermarking that are difficult to be computed analytically. A series of empirical investigations are performed to analyze the performance of the genetically evolved perceptual shaping functions (GPSFs) using standard benchmark, which shows the effectiveness of our approach.