{"title":"Multiple-Image Fusion Encryption (MIFE) Using Discrete Cosine Transformation (DCT) and Pseudo Random Number Generators","authors":"Lee Mariel Heucheun Yepdia, A. Tiedeu, Z. Lachiri","doi":"10.5772/intechopen.92369","DOIUrl":null,"url":null,"abstract":"This chapter proposes a new multiple-image encryption algorithm based on spectral fusion of watermarked images and new chaotic generators. Logistic-May (LM), May-Gaussian (MG), and Gaussian-Gompertz (GG) were used as chaotic generators for their good properties in order to correct the flaws of 1D chaotic maps (Logistic, May, Gaussian, Gompertz) when used individually. Firstly, the discrete cosine transformation (DCT) and the low-pass filter of appropriate sizes are used to combine the target watermarked images in the spectral domain in two different multiplex images. Secondly, each of the two images is concatenated into blocks of small size, which are mixed by changing their position following the order generated by a chaotic sequence from the Logistic-May system (LM). Finally, the fusion of both scrambled images is achieved by a nonlinear mathematical expression based on Cramer’s rule to obtain two hybrid encrypted images. Then, after the decryption step, the hidden message can be retrieved from the watermarked image without any loss. The security analysis and experimental simulations confirmed that the proposed algorithm has a good encryption performance; it can encrypt a large number of images combined with text, of different types while maintaining a reduced Mean Square Error (MSE) after decryption.","PeriodicalId":48501,"journal":{"name":"International Journal of Multimedia Information Retrieval","volume":"6 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Multimedia Information Retrieval","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.5772/intechopen.92369","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 2
Abstract
This chapter proposes a new multiple-image encryption algorithm based on spectral fusion of watermarked images and new chaotic generators. Logistic-May (LM), May-Gaussian (MG), and Gaussian-Gompertz (GG) were used as chaotic generators for their good properties in order to correct the flaws of 1D chaotic maps (Logistic, May, Gaussian, Gompertz) when used individually. Firstly, the discrete cosine transformation (DCT) and the low-pass filter of appropriate sizes are used to combine the target watermarked images in the spectral domain in two different multiplex images. Secondly, each of the two images is concatenated into blocks of small size, which are mixed by changing their position following the order generated by a chaotic sequence from the Logistic-May system (LM). Finally, the fusion of both scrambled images is achieved by a nonlinear mathematical expression based on Cramer’s rule to obtain two hybrid encrypted images. Then, after the decryption step, the hidden message can be retrieved from the watermarked image without any loss. The security analysis and experimental simulations confirmed that the proposed algorithm has a good encryption performance; it can encrypt a large number of images combined with text, of different types while maintaining a reduced Mean Square Error (MSE) after decryption.
期刊介绍:
Aims and Scope
The International Journal of Multimedia Information Retrieval (IJMIR) is a scholarly archival journal publishing original, peer-reviewed research contributions. Its editorial board strives to present the most important research results in areas within the field of multimedia information retrieval. Core areas include exploration, search, and mining in general collections of multimedia consisting of information from the WWW to scientific imaging to personal archives. Comprehensive review and survey papers that offer up new insights, and lay the foundations for further exploratory and experimental work, are also relevant.
Relevant topics include
Image and video retrieval - theory, algorithms, and systems
Social media interaction and retrieval - collaborative filtering, social voting and ranking
Music and audio retrieval - theory, algorithms, and systems
Scientific and Bio-imaging - MRI, X-ray, ultrasound imaging analysis and retrieval
Semantic learning - visual concept detection, object recognition, and tag learning
Exploration of media archives - browsing, experiential computing
Interfaces - multimedia exploration, visualization, query and retrieval
Multimedia mining - life logs, WWW media mining, pervasive media analysis
Interactive search - interactive learning and relevance feedback in multimedia retrieval
Distributed and high performance media search - efficient and very large scale search
Applications - preserving cultural heritage, 3D graphics models, etc.
Editorial Policies:
We aim for a fast decision time (less than 4 months for the initial decision)
There are no page charges in IJMIR.
Papers are published on line in advance of print publication.
Academic, industrial researchers, and practitioners involved with multimedia search, exploration, and mining will find IJMIR to be an essential source for important results in the field.