High Capacity Image Steganography using Pixel Value Differencing Method with Data Compression using Neural Network
Jayeeta Majumder1, Chittaranjan Pradhan2
1Jayeeta Majumder*, Computer Science & Engineering, Haldia Institute of Technology, Haldia, West Bengal.
2Chittaranjan Pradhan, Computer Science & Engineering, KIIT University, Bhubaneswar, Odissa.
Manuscript received on September 17, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 1800-1804 | Volume-8 Issue-12, October 2019. | Retrieval Number: L28391081219/2019©BEIESP | DOI: 10.35940/ijitee.L2839.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Digital Market Is Rapidly Growing Day By Day. So, Data Hiding Is Going To Increase Its Importance. Information Can Be Hidden In Different Embedding Mediums, Known As Carriers By Using Steganography Techniques. The Carriers Are Different Multimedia Medium Such As Images, Audio Files, Video Files, And Text Files .There Are Several Techniques Present To Achieve Data Hiding Like Least Significant Bit Insertion Method And Transform Domain Technique. The Data Hidden Capacity Inside The Cover Image Totally Depends On The Properties Of The Image Like Number Of Noisy Pixels. Data Compression Provides To Hide Large Amount Of Secret Data To Increase The Capacity And The Image Steganography Based On Any Neural Network Provides That The Size And Quality Of The Stego-Image Remains Unaltered After Data Embedding. In This Paper We Propose A New Method Combined With Data Compression Along With Data Embedding Technique And After Embedding To Maintain The Quality The Communication Channel Use The Neural Network. The Compression Technique Increase The Data Hiding Capacity And The Use Of Neural Network Maintain The Flow Of Data Processing Signal
Keywords: Image Steganography, Data Compression, Arithmetic Coding, Pixel Value Differencing, Neural Network
Scope of the Article: Image Processing and Pattern Recognition