Name
Abstract | ||
|---|---|---|
Simultaneous MREG and EEG recordings are vastly used in neurobiology, but so far they are stored and handled as separate files. This paper proposes a method to combine those two entities with the objective of establishing data management efficiency, while secondary objectives are confidentiality, availability and reliability in data. To be more specific, it is a reversible data hiding method for hiding EEG in MREG with the ability of fully recovering MREG and the embedded EEG signal. It is based on histogram shifting, exploiting data quantization and Region of Interest segmentation. The embedding procedure maintains temporal synchronization between EEG and 32-bit MREG making it a novel data hiding application. It is demonstrated through experiments that MREG maintains high perceptual fidelity and also verified that after EEG extraction and acquisition of every electrodeâs sample, MREG is fully reversed to its exact initial state. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.5220/0005665700580067 | HEALTHINF |
Field | DocType | Citations |
Computer vision,Histogram,Data mining,Synchronization,Fidelity,Segmentation,Computer science,Information hiding,Artificial intelligence,Region of interest,Data management,Electroencephalography | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angelos Fylakis | 1 | 13 | 3.67 |
| Anja Keskinarkaus | 2 | 58 | 7.17 |
| Vesa Kiviniemi | 3 | 449 | 29.75 |
| Tapio Seppänen | 4 | 604 | 84.33 |