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Medical image watermarking for ownership & tamper detection

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Abstract

Image watermarking can provide ownership identification as well as tamper protection. Transform domain based image watermarking has been proven to be more robust than the spatial domain watermarking against different signal processing attacks. On the other hand, tamper detection is found to be working well in spatial domain. In the proposed work, the focus is on the improvement of the medical image watermarking by incorporating the concept of multiple watermarking of the host image. The principal components (PC) based insertion make the scheme secured towards ownership attack. On the other hand, LZW (Lempel–Ziv–Welch) based fragile watermarking is used to hide compressed image’s ROI (region of interest) to tackle the intentional tampering attacks. The ROI based watermark generation provides the complete reversibility of the ROI. In this way, proposed scheme provides perfect reversibility of ROI, good imperceptibility in addition to satisfactory robustness. The tamper handing ability of proposed scheme is also tested against various attacks, which turns out to be quite good. The proposed scheme is found to be more useful, when compared with recently proposed schemes in term of features and usefulness.

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Abbreviations

LZW:

Lempel–Ziv–Welch

ROI:

Region of Interest

PC:

Principal Component

RONI:

Region of Non-Interest

DWT:

Discrete Wavelet transform

SVD:

Singular value decomposition

2D:

Two-Dimension

LSB:

Least significant bit

Hex:

Hexadecimal

SHA:

Secure Hash Algorithm

HH:

High-High

LL:

Low-Low

LH:

Low-High

HL:

High-Low

WM:

Watermarked

WM (R):

Watermarked (Robust)

WM (R&F):

Watermarked (Robust & Fragile)

PSNR :

Peak Signal to Noise Ratio

NC :

Normalized correlation

EW:

Extracted watermark

LDOPA:

Low-distortion overflow processing algorithm

U.S.:

United States

JPEG:

Joint Photographic Experts Group

QF:

Quality Factor

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  1. College of Computer Science and Information System, Umm Al-Qura University, Makkah, Saudi Arabia

    Hanan S. Alshanbari

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  1. Hanan S. Alshanbari
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Correspondence to Hanan S. Alshanbari.

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Alshanbari, H.S. Medical image watermarking for ownership & tamper detection. Multimed Tools Appl 80, 16549–16564 (2021). https://doi.org/10.1007/s11042-020-08814-9

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  • DOI: https://doi.org/10.1007/s11042-020-08814-9

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