Geometrically Robust Digital Image Watermarking Based on Zernike Moments and FAST Technique

Dwivedi, Ranjana; Srivastava, Vinay Kumar

doi:10.1007/978-981-19-2631-0_58

Cited by 4 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This algorithm has good robustness but poor resistance to cropping attacks, high computational cost, and does not take into account the problem of missing pixel values resulting in missing extracted watermarks due to rotation attacks. Dwivedi et al [26] proposed a robust image watermarking scheme by combining Zernike moments and FAST. The image robust feature points are extracted by the FAST method.…”

Section: Introductionmentioning

confidence: 99%

“…Since local image feature descriptors are invariant and distinguishable, existing watermarking algorithms are often combined with feature descriptors [24]. Commonly used feature descriptors are SIFT (Scale Invariant Feature Transform) [20,25,26], SURF (Speeded Up Robust Features) [22][23][24], FAST (Features from accelerated segment test) [26], Daisy [27] etc. Fang et al [20] used the SIFT algorithm to extract image features and perform bandelet transform and DCT on their characteristics to obtain the feature vector of medical images.…”

Section: Introductionmentioning

confidence: 99%

“…Dwivedi et al. [26] proposed a robust image watermarking scheme by combining Zernike moments and FAST. The image robust feature points are extracted by the FAST method.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Yuan,

Li,

Liu

et al. 2024

CAAI Trans on Intel Tech

View full text Add to dashboard Cite

In the intricate network environment, the secure transmission of medical images faces challenges such as information leakage and malicious tampering, significantly impacting the accuracy of disease diagnoses by medical professionals. To address this problem, the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi‐stage discrete wavelet transform (DWT), Daisy descriptor, and discrete cosine transform (DCT). The algorithm initially encrypts the original medical image through DWT‐DCT and Logistic mapping. Subsequently, a 3‐stage DWT transformation is applied to the encrypted medical image, with the centre point of the LL3 sub‐band within its low‐frequency component serving as the sampling point. The Daisy descriptor matrix for this point is then computed. Finally, a DCT transformation is performed on the Daisy descriptor matrix, and the low‐frequency portion is processed using the perceptual hashing algorithm to generate a 32‐bit binary feature vector for the medical image. This scheme utilises cryptographic knowledge and zero‐watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image, which meets the basic requirements of medical image watermarking. The embedding and extraction of watermarks are accomplished in a mere 0.160 and 0.411s, respectively, with minimal computational overhead. Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks, with a notable performance in resisting rotation attacks.

show abstract

Section: Introductionmentioning

confidence: 99%