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In this paper, a new method based on a hybrid model composed of a genetic algorithm and a chaotic function is proposed for image encryption. In the proposed method, first a number of encrypted images are constructed using the original image with the help of the chaotic function. In the next stage, these encrypted images are employed as the initial population for starting the operation of the genetic algorithm. In each stages of the genetic algorithm, the answer obtained from previous iteration is optimized so that the best encrypted image with the highest entropy and the lowest correlation coefficient among adjacent pixels is produced.
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