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Reversible image steganography using roi & roni / Lim Jee Chao

By:

Lim Jee Chao [author.]

Material type: Text

text
text

Media type:

unmediated
computer

Carrier type:

volume
computer disc

ISBN:

THE0009647 (Local)

Subject(s):

Dissertation note: Project paper (Bachelor of Computer Science (Software Engineering) With Honours -- Universiti Malaysia Pahang - 2015 Abstract: Reversible steganography allows to recover of original image without any distortion when the embedded secret message has extracted. This research was tested with four different image and one storage image. The sample image is divided into three type of region which are Region of Interest (ROI), Region of Non-Interest (RONI) and untouchable region. This research using the technique of finding the ROI and RONI of the cover image to find position to embed the message and recover the original image. During embedding process, the RONIs’ bits are stored into the storage image known as sample_image. Next, the ROIs’ bits are stored into RONI so that it can be recovered during extraction process. Sender select the x-coordinate and y-coordinate to embed the secret information into the ROI2. Sender also need embed the secret key in the RONI2 image which can help to secure the secret information. After that, stego-image was generated after ROI and RONI embedded. In extraction process, receiver need to extract the secret key to decrypt the secret message. For reversible process, ROIs and RONIs were reversed to original bits. Peak Signal-to-Noise Ratio (PSNR) value was used to measure the quality of stego-image and similarity of original image and recover image. The value of PSNR of the four selected sample image is between 52.60dB to 52.62dB. Histogram of original image, stego-image and recover image are generated for visual difference between original image, stego-image and recover image. In conclusion, this proposed method has proved a better approach compared to previous work in terms of selecting a position to embed by using ROI and RONI.

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Holdings ( 2 )
Title notes ( 4 )

Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Thesis	UMPLIB PEKAN	FSKKP .J56 2019 r Bc. (Browse shelf(Opens below))	Not for loan		T000002369
Thesis	UMPLIB PEKAN	CD13350 (Browse shelf(Opens below))	Not for loan		T000002370

Faculty of Computer Systems and Software Engineering

Project paper (Bachelor of Computer Science (Software Engineering) With Honours -- Universiti Malaysia Pahang - 2015

Bibliography : page 65-66

Reversible steganography allows to recover of original image without any distortion when the embedded secret message has extracted. This research was tested with four different image and one storage image. The sample image is divided into three type of region which are Region of Interest (ROI), Region of Non-Interest (RONI) and untouchable region. This research using the technique of finding the ROI and RONI of the cover image to find position to embed the message and recover the original image. During embedding process, the RONIs’ bits are stored into the storage image known as sample_image. Next, the ROIs’ bits are stored into RONI so that it can be recovered during extraction process. Sender select the x-coordinate and y-coordinate to embed the secret information into the ROI2. Sender also need embed the secret key in the RONI2 image which can help to secure the secret information. After that, stego-image was generated after ROI and RONI embedded. In extraction process, receiver need to extract the secret key to decrypt the secret message. For reversible process, ROIs and RONIs were reversed to original bits. Peak Signal-to-Noise Ratio (PSNR) value was used to measure the quality of stego-image and similarity of original image and recover image. The value of PSNR of the four selected sample image is between 52.60dB to 52.62dB. Histogram of original image, stego-image and recover image are generated for visual difference between original image, stego-image and recover image. In conclusion, this proposed method has proved a better approach compared to previous work in terms of selecting a position to embed by using ROI and RONI.