000			02920ntm a2200373 i 4500
999			_c99502 _d99508
003			MY-KuUP
005			20251125110737.0
006			t||||fr|||| 000 0
007			ta
008			230508t20192019my a|||fr|||| 000 0 eng d
020			_aTHE0009647 (Local) _qHardback
040			_aUMP _beng _cUMP _erda
090			_aFSKKP .J56 2019 r Bc.
100	1		_aLim Jee Chao, _eauthor.
245	1	0	_aReversible image steganography using roi & roni / _cLim Jee Chao
264		1	_aKuantan, Pahang : _bUMP, _c2019
264		4	_c©2019
300			_axii, 68 pages :
336			_2rdacontent _atext
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
337			_2rdamedia _acomputer
338			_2rdacarrier _avolume
338			_2rdacarrier _acomputer disc
347			_2rda _atext file _bPDF
500			_aFaculty of Computer Systems and Software Engineering
502			_aProject paper (Bachelor of Computer Science (Software Engineering) With Honours -- Universiti Malaysia Pahang - 2015
504			_aBibliography : page 65-66
520	3		_aReversible 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.
610	2	0	_aFaculty of Computer Systems and Software Engineering _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS