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Steganography on JPEG Image for Minimum Energy


Affiliations
1 Karunya University, Coimbatore, India
2 Computer Science and Engineering Department in Karunya University, Coimbatore, India
     

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JPEG images are having small capacity to hide information. It’s because of the limited redundancy. The high capacity steganography scheme for JPEG is thus introduced to increase that capacity. The main objective of this paper is to increase the hiding capacity by solving the problems due to limited redundancy and bitstream truncation .After that image compression will be done for the purpose of sending or transferring the data. The system is used to deliver data to the intended receiver reliably and secretly. Quantization may cause information loss in JPEG compression. So JPEG compression computations are mapped using the minimum integer and fractional bit-widths needed in view of other approximations inherent in the compression process and choice of image quality parameters. Range analysis determines the integer bit widths and precision analysis determines the fractional bit widths needed for the JPEG compression. Optimized JPEG implementations reduces the amount of energy consumed for the compression process and results in larger compressed image files.

Keywords

Image Coding, Fixed Point Arithmetic, JPEG Compression, Information Embedding.
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  • Steganography on JPEG Image for Minimum Energy

Abstract Views: 242  |  PDF Views: 1

Authors

Anju Vincent
Karunya University, Coimbatore, India
M. Roshni Thanka
Computer Science and Engineering Department in Karunya University, Coimbatore, India
Ansu Liz Thomas
Computer Science and Engineering Department in Karunya University, Coimbatore, India

Abstract


JPEG images are having small capacity to hide information. It’s because of the limited redundancy. The high capacity steganography scheme for JPEG is thus introduced to increase that capacity. The main objective of this paper is to increase the hiding capacity by solving the problems due to limited redundancy and bitstream truncation .After that image compression will be done for the purpose of sending or transferring the data. The system is used to deliver data to the intended receiver reliably and secretly. Quantization may cause information loss in JPEG compression. So JPEG compression computations are mapped using the minimum integer and fractional bit-widths needed in view of other approximations inherent in the compression process and choice of image quality parameters. Range analysis determines the integer bit widths and precision analysis determines the fractional bit widths needed for the JPEG compression. Optimized JPEG implementations reduces the amount of energy consumed for the compression process and results in larger compressed image files.

Keywords


Image Coding, Fixed Point Arithmetic, JPEG Compression, Information Embedding.