ya que 05 febrero 2011 :
Vista(s): 401 (3 ULiège)
Descargar(s): 129 (0 ULiège)
Elaheh Agha Mohammadi & Mehdi Sadegh Zadeh

The production of the initial population and Mandelbrot algorithm by using genetic set to encrypt Image

Open Access

Documento adjunto(s)

Version PDF originale


Nowadays, finding a way to secure media is common with the growth of digital media. An effective method for the secure transmission of images can be found in the field of visual cryptography. There is a growing interest in the use of visual cryptography in security application.Since this method is used for secure transmission of images, many of the methods are developed based on the original algorithm proposed by Naor and Shamir in 1994.In this paper, a new hybrid model is used in cryptography of images which is composed of Mandelbrot algorithm and genetic algorithm. In the early stages of proposal, a number of encrypted images are made by using the Mandelbrot algorithm and the original picture and in the next stage, these encrypted images are used as the initial population for the genetic algorithm.At each stage of the genetic algorithm, the answer of previous iterations is optimized to get the best encoding image. Also, in the proposed method, we can achieve the decoded image by a reverse operation from the genetic algorithm. The best encrypted image is an image with high entropy and low correlation coefficient. According to the entropy and correlation coefficient of the proposed method compared with existing methods, it is observed that our method gets better results in both of them.

Keywords : fractal, genetic algorithm, Mandelbrot function, reversible genetic algorithm, visual cryptography

Para citar este artículo

Elaheh Agha Mohammadi & Mehdi Sadegh Zadeh, «The production of the initial population and Mandelbrot algorithm by using genetic set to encrypt Image», Bulletin de la Société Royale des Sciences de Liège [En ligne], Volume 85 - Année 2016, Actes de colloques, Special edition, 935 - 951 URL : https://popups.uliege.be:443/0037-9565/index.php?id=5751.

Acerca de: Elaheh Agha Mohammadi

Graduate Student Artificial Intelligence Computer Engineer, Islamic Azad University, Science and Research of Bushehr, Iran

Acerca de: Mehdi Sadegh Zadeh

Department of Computer Engineer, Islamic Azad University of Mahshahr, Iran