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  • 标题:Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region
  • 其他标题:Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region
  • 本地全文:下载
  • 作者:Sahib Khan ; Tiziano Bianchi
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2018
  • 卷号:8
  • 期号:1
  • 页码:379-389
  • DOI:10.11591/ijece.v8i1.pp379-389
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, in order to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method.
  • 其他摘要:This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, in order to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method.
  • 关键词:Image Processing; Image Steganography;;Ant colony optimization; Pheromone matrix; LSB Steganography; Edge detection; Steganalysis
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