Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/588405
Title: | A Secured and High Capacity Reversible Data Embedding Technique Using Integer Wavelet Transform |
Researcher: | Amishi Mahesh Kapadia |
Guide(s): | Nithyanandam, P |
Keywords: | Computer Science Computer Science Interdisciplinary Applications Engineering and Technology |
University: | Vellore Institute of Technology, Vellore |
Completed Date: | 2024 |
Abstract: | In the growing era of digitalized communication, secure transmission and storage newlineare the key needs of the hour due to voluminous digital transmission. Information hiding newlineis one of the essential aspects with respect to the protection of data against unauthorized newlineaccess. Reversible data hiding is one of the emerging areas where the degradation of newlinethe original image used for embedding and secret information at the receiver end is not newlineacceptable. The existing system has multiple issues and challenges, like limited capacity, newlinereversibility with embedding algorithms, security, and usage of auxiliary data, to newlinemention a few. The proposed system is focused on enhancing capacity and improved newlinesecurity, so information is not misused. In the first model, integer wavelet transform newlineis utilized to resolve the issue of floating point and negative coefficients along with a newlinemodified least significant bit embedding algorithm, which improves the capacity. In the newlinesecond model, along with wavelets, dual embedding is implemented, which increases newlinecapacity by using matrix embedding, and on extraction, both secret and cover images newlineare intact. In the third model, a recursive embedding technique is used, which significantly newlineenhances the capacity and substantial security using the Arnold transform, which newlineis the key to retrieving information and data that cannot be extracted otherwise. The newlineproposed system uses a standard benchmark data set, fingerprint, knee X-ray images, newlineand BOSS dataset. It has been analyzed using Signal to Noise Ratio, Image Fidelity, newlineHellinger s Distance, Structural Similarity, and Normalized Cross Correlation. The hybrid newlinecombination has provided a system with high capacity and security newline newline |
Pagination: | i-xv,111 |
URI: | http://hdl.handle.net/10603/588405 |
Appears in Departments: | School of Computing Science and Engineering VIT-Chennai |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 115.68 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 192.84 kB | Adobe PDF | View/Open | |
03_content.pdf | 51.66 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 62.17 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 298 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 150.23 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 278.02 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.22 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.53 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 1.29 MB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 51.57 kB | Adobe PDF | View/Open | |
12_annexure.pdf | 94.07 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 166.73 kB | Adobe PDF | View/Open |
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