Contourlet-2.3 Retrieval Algorithm Using Absolute Mean Energy and Kurtosis Features

Chen, Xinwu; Liu, Liwei

doi:10.1007/978-3-642-19712-3_39

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2022

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“…Next step after computing the size of data that need to hide is choosing a suitable CT sub-bands coefficients from the last level (high pass region) by computing the energy for each sub-band and choose less one and so on in order to decrease the distorting that is resulted from embedding secret message in cover audio. Equation 1 [19] will be used to calculate the energy of contourlet sub-bands as: Fig. 3.…”

Section: Proposed Schemementioning

confidence: 99%

High Capacity Audio Steganography Based on Contourlet Transform

Hameed

2022

Tikrit j. eng. sci.

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A B S T R A C TThe science of hiding information behind other cover media file is known steganography. Audio steganography means that a secret message is hidden by embedding it in an audio file. This paper presents a new audio steganography approach that is used the contourlet transform to hide a speech and image in an audio signal. The cover audio signal is modified to be suitable as input to contourlet transform and then secret data embed to the subbands of contourlet transform. The results showed high hiding capacity of data up to 90% of cover audio file size. In addition, performance analysis by measures factors: Normalized Correlation (NC), Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR) appears good quality results for both stego and secret data.

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Section: Proposed Schemementioning

confidence: 99%

High Capacity Audio Steganography Based on Contourlet Transform

Hameed

2022

Tikrit j. eng. sci.

View full text Add to dashboard Cite

show abstract

Contourlet-2.3 Retrieval Algorithm Using Absolute Mean Energy and Kurtosis Features

Cited by 1 publication

References 6 publications

High Capacity Audio Steganography Based on Contourlet Transform

High Capacity Audio Steganography Based on Contourlet Transform

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