Evolutionary algorithms for fast and accurate watermark retrieval

A watermark hidden in an image is retrieved differently from the original watermark due to the frequently used rounding approach. The simple rounding will cause numerous errors in the embedded watermark especially when it is large. Evolutionary algorithms (EA) are used to correct the rounding errors. The main issue before applying EAs to reduce the rounding errors is that the embedded data should be retrieved correctly. Evolutionary algorithms are commonly used as adaptive approaches that provide a randomized, parallel and global search method based on the mechanics of natural selection and natural genetics in order to find solutions of problems. We present the application of genetic algorithms (GA), differential evolution (DE) and simplified threshold accepting algorithm (STA) to enhance the watermark retrieval. Experimental results show that STA converges faster to the optimal solution than DE, which in turn converges faster than GA.