Block-Wise Authentication and Recovery Scheme for Medical Images Focusing on Content Complexity

Title
Block-Wise Authentication and Recovery Scheme for Medical Images Focusing on Content Complexity
Publication Date
2020
Author(s)
Tohidi, Faranak
Paul, Manoranjan
Hooshmandasl, Mohammad Reza
Chakraborty, Subrata
( author )
OrcID: https://orcid.org/0000-0002-0102-5424
Email: schakra3@une.edu.au
UNE Id une-id:schakra3
Pradhan, Biswajeet
Editor
Editor(s): Joel Janek Dabrowski, Ashfaqur Rahman and Manoranjan Paul
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Springer
Place of publication
Cham, Switzerland
Series
Lecture Notes in Computer Science
DOI
10.1007/978-3-030-39770-8_7
UNE publication id
une:1959.11/51905
Abstract

Digital images are used to transfer most critical data in areas like medical, research, business, military, etc. The images transfer takes place over an unsecured Internet network. Therefore, there is a need for reliable security and protection for these sensitive images. Medical images play an important role in the field of Telemedicine and Tele surgery. Thus, before making any diagnostic decisions and treatments, the authenticity and the integrity of the received medical images need to be verified to avoid misdiagnosis. This paper proposes a block-wise and blind fragile watermarking mechanism for medical image authentication and recovery. By eliminating embedded insignificant data and considering different content complexity for each block during feature extraction and recovery, the capacity of data embedding without loss of quality is increased. This new embedding watermark method can embed a copy of the compressed image inside itself as a watermark to increase the recovered image quality. In our proposed hybrid scheme, the block features are utilized to improve the efficiency of data concealing for authentication and reduce tampering. Therefore, the scheme can achieve better results in terms of the recovered image quality and greater tampering protection, compared with the current schemes.

Link
Citation
Image and Video Technology: PSIVT 2019, p. 86-99
ISBN
9783030397708
9783030397692
Start page
86
End page
99

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