Rachmawanto, Eko Hari (2012) Steganography for securing image data using hybrid SLT and DCT. Masters thesis, Universiti Teknikal Malaysia Melaka.
Text (24 Pages)
Steganography for securing image data using hybrid SLT and DCT.pdf - Submitted Version Download (1MB) |
|
Text (Full Text)
Steganography for securing image data using hybrid SLT and DCT.pdf - Submitted Version Restricted to Registered users only Download (5MB) |
Abstract
This study proposes a hybrid technique in securing image data that will be applied in telemedicine in future. Based on the web-based ENT diagnosis system using Virtual Hospital Server (VHS), patients are able to submit their physiological signals and multimedia data through the internet. In telemedicine system, image data need more secure to protect data patients in web. Cryptography and steganography are techniques that can be used to secure image data implementation. In this study, steganography method hos been applied using hybrid between Discrete Cosine Transform (OCT) and Slantlet Transform (SLT) technique. DCT is calculated on blocks of independent pixels, a coding error causes discontinuity between blocks resulting in annoying blocking artifact. While SLT applies on entire image and offers better energy compaction compare to OCT without any blocking artifact. Furthermore, SLT splits component into numerous frequency bands called sub bands or octave bands. It is known that SLT is a better than DWT based scheme and better time localization. Weakness of DCT is eliminated by SLT that employ an improved version of the usual Discrete Wavelet Transform (DWT). Some comparison of technique is included in this study to show the capability of the hybrid SLT and OCT. Experimental results show that optimum imperceptibility is achieved.
Item Type: | Thesis (Masters) |
---|---|
Uncontrolled Keywords: | Hybrid technique, Securing image data, Telemedicine |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics |
Divisions: | Library > Tesis > FTMK |
Depositing User: | MUHAMAD HAFEEZ ZAINUDIN |
Date Deposited: | 13 Dec 2024 08:55 |
Last Modified: | 13 Dec 2024 08:55 |
URI: | http://eprints.utem.edu.my/id/eprint/28232 |
Statistic Details: | View Download Statistic |
Actions (login required)
View Item |