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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM19290

Data Compression and Decompression with Image steganography using api

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM19290

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AG

Aadesh Garg

AP

Amisha Prajapati

Al

Amisha linjhara

AS

Ananya Shrivastava

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Abstract

Image Steganography is the process of hiding information which can be text, image or video inside a cover image. The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, which has emerged as a powerful tool in various applications including image steganography, has received increased attention recently. The main goal of this paper is to explore and discuss various deep learning methods available in image steganography field. This paper presents a review kind of data compression techniques. Data compression is widely used by the community because through a compression we can save storage. Data compression can also speed up a transmission of data from one person to another. In performing a compression requires a method of data compression that can be used, the method can then be used to compress a data. Data that can be compressed not only text data but can be images and video. Keyboard: Image steganography, GAN steganography, CNN steganography, information hiding, image data hiding Data Compression, compression techniques, lossless compression, Huffman, Shannon Fano, Tunstall, RLE, LZW.

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Cite This Article

Aadesh Garg, Amisha Prajapati, Amisha linjhara, Ananya Shrivastava, "Data Compression and Decompression with Image steganography using api," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023.

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Publication Date

4/20/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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