A DWT-SVD based robust digital watermarking for medical image security
TL;DR: In this article, a blind watermarking approach for medical image protection is proposed, which consists of the Electronic Patient Record and the image acquisition data, and the watermark is then integrated into the least significant bits of the S component obtained by combining the parity of the successive coefficients.
About: This article is published in Forensic Science International.The article was published on 2021-01-13. It has received 45 citations till now. The article focuses on the topics: Watermark & Digital watermarking.
Citations
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TL;DR: A Pigeon Inspired Optimization with Encryption-based Secure Medical Image Management (PIOE-SMIM) technique is presented and the results highlighted the supremacy of the PIOE -SMIM model over other techniques.
Abstract: Presently, technological advancements in the healthcare sector pose a challenging problem relevant to the security and privacy of health-related applications. Medical images can be considered significant and sensitive data in the medical informatics system. In order to transmit medical images in an open medium, the design of secure encryption algorithms becomes essential. Encryption can be considered one of the effective solutions for accomplishing security. Although numerous models have existed in the literature, they could not adaptable to the rising number of medicinal images in the health sector. At the same time, the optimal key generation process acts as a vital part in defining the performance of the encryption techniques. Therefore, this article presents a Pigeon Inspired Optimization with Encryption-based Secure Medical Image Management (PIOE-SMIM) technique. The proposed PIOE-SMIM approach majorly concentrates on the development of secret share creation (SSC) and the encryption process. At the initial stage, the medical images are converted into a collection of 12 shares using the SSC approach. In addition, an elliptic curve cryptography (ECC) scheme is employed for the encryption process. In order to optimum key creation procedure in the ECC model, the PIO technique is exploited with the aim of maximizing PSNR. Finally, on the receiver side, the decryption and share reconstruction processes are performed to construct the original images. The PIOE-SMIM model displayed an enhanced PSNR of 59.37 dB in image 1. Improved PSNR of 59.53 dB is given for image 5 using the PIOE-SMIM model. For demonstrating an enhanced performance of the PIOE-SMIM method, a widespread experimental study is made and the results highlighted the supremacy of the PIOE-SMIM model over other techniques.
68 citations
TL;DR: This innovative approach consists precisely of carefully inserting hospital signature information and patient data into the medical image to protect medical images and ensures information integrity, patient confidentiality when sharing data, and robustness to several conventional attacks.
32 citations
TL;DR: In this article , the authors presented a trust-driven privacy method using encryption and steganography for real-time Internet of Vehicles (IoV) communication. But the proposed method is not suitable for the use of autonomous vehicles.
26 citations
TL;DR: In this article , the authors proposed color image authentication based on blind fragile image watermarking for tamper detection and self-recovery named AuSR1, which divides each channel of the cover image into non-overlapping blocks with the size of 2 × 2 pixels.
18 citations
TL;DR: In this article, two watermarking schemes for retinal image protection are proposed, which are implemented in the three insertion domains: spatial, frequency and multi-resolution domain, respectively, for the spatial domain, the watermark will be integrated into the R, G and B values of the image.
Abstract: In order to improve the security of images exchanged in telemedicine, we propose in this paper, 2 watermarking schemes for retinal image protection; each scheme will be declined into 2 variants. The integration of the watermark will be performed by combining the parity of the successive values; each variant will represent a different combination. These approaches will be implemented in the three insertion domains: spatial, frequency and multi-resolution domain. For the spatial domain, the watermark will be integrated into the R, G and B values of the image. In the frequency domain, the watermark bits will be substituted to the DCT coefficient’s least significant bit. For the multi-resolution domain insertion, after calculating a DWT, the obtained LL sub-band coefficients will be used for the integration process. After comparing our approaches to the different recent works in the three domains; the obtained results demonstrate that our first proposed approach offers a good imperceptibility for the frequency and spatial domains insertion. However, using 512 × 512 images for our experiments considerably reduces the capacity of our approach in the frequency domain.
17 citations
References
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TL;DR: Experimental results demonstrate that the suggested watermarking technique archives high robustness against attacks in comparison to the other scheme for medical images, and verification its robustness for various attacks while maintaining imperceptibility, security and compression ratio.
160 citations
TL;DR: Robustness of the scheme is better than existing scheme for similar set of medical images in terms of normalized correlation coefficient (NCC) and bit-error-rate (BER) and performance comparison of proposed scheme with existing schemes shows proposed scheme has better robustness against different types of attacks.
Abstract: In this paper, a blind image watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed. In this scheme, DWT is applied on ROI (region of interest) of the medical image to get different frequency subbands of its wavelet decomposition. On the low frequency subband LL of the ROI, block-SVD is applied to get different singular matrices. A pair of elements with similar values is identified from the left singular value matrix of these selected blocks. The values of these pairs are modified using certain threshold to embed a bit of watermark content. Appropriate threshold is chosen to achieve the imperceptibility and robustness of medical image and watermark contents respectively. For authentication and identification of original medical image, one watermark image (logo) and other text watermark have been used. The watermark image provides authentication whereas the text data represents electronic patient record (EPR) for identification. At receiving end, blind recovery of both watermark contents is performed by a similar comparison scheme used during the embedding process. The proposed algorithm is applied on various groups of medical images like X-ray, CT scan and mammography. This scheme offers better visibility of watermarked image and recovery of watermark content due to DWT-SVD combination. Moreover, use of Hamming error correcting code (ECC) on EPR text bits reduces the BER and thus provides better recovery of EPR. The performance of proposed algorithm with EPR data coding by Hamming code is compared with the BCH error correcting code and it is found that later one perform better. A result analysis shows that imperceptibility of watermarked image is better as PSNR is above 43 dB and WPSNR is above 52 dB for all set of images. In addition, robustness of the scheme is better than existing scheme for similar set of medical images in terms of normalized correlation coefficient (NCC) and bit-error-rate (BER). An analysis is also carried out to verify the performance of the proposed scheme for different size of watermark contents (image and EPR data). It is observed from analysis that the proposed scheme is also appropriate for watermarking of color image. Using proposed scheme, watermark contents are extracted successfully under various noise attacks like JPEG compression, filtering, Gaussian noise, Salt and pepper noise, cropping, filtering and rotation. Performance comparison of proposed scheme with existing schemes shows proposed scheme has better robustness against different types of attacks. Moreover, the proposed scheme is also robust under set of benchmark attacks known as checkmark attacks.
157 citations
TL;DR: The obtained results show that the approach offers good imperceptibility and generates watermarking images robust against various attacks with a high-quality watermark.
102 citations
TL;DR: Simulation outcomes conducted on different types of medical images disclose that the proposed scheme demonstrates superior transparency and robustness against signal and compression attacks compared with the related hybrid optimized algorithms.
94 citations
22 Sep 2013
TL;DR: This work proposes a new, more global, optimization framework for separating two overlapping trees within medical images and applies this approach for the separation of arteriovenous trees in low-contrast color fundus images.
Abstract: While many approaches exist for the automated segmentation of retinal vessels in fundus photographs, limited work has focused on the problem of separating the arterial from the venous trees. The few existing approaches that do exist for separating arteries from veins are local and/or greedy in nature, making them susceptible to errors or limiting their applicability to only the very largest vessels. In this work, we propose a new, more global, optimization framework for separating two overlapping trees within medical images and apply this approach for the separation of arteriovenous trees in low-contrast color fundus images. In particular, our approach has two stages. The first stage is to generate a vessel potential connectivity map (VPCM) consisting of vessel segments and the potential connectivity between them. The second stage is to separate the VPCM into multiple anatomical trees using a graph-based meta-heuristic algorithm. Based on a graph model, the algorithm first uses local knowledge and global constraints of the vasculature to generate near-optimal candidate solutions, and then obtains the final solution based on global costs. We test the algorithm on 48 low-contrast fundus images and the promising results suggest its applicability and robustness.
93 citations