divyanshu awasthi
Verified @gmail.com
Research scholar
RESEARCH INTERESTS
Signal and image processing
Scopus Publications
Scopus Publications
Divyanshu Awasthi, Priyank Khare, and Vinay Kumar Srivastava
Elsevier BV
Divyanshu Awasthi, Priyank Khare, Vinay Kumar Srivastava, and Amit Kumar Singh
Elsevier BV
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Anurag Tiwari, Divyanshu Awasthi, and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi, Anurag Tiwari, Priyank Khare, and Vinay Kumar Srivastava
Elsevier BV
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi, Priyank Khare, and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi, Priyank Khare, and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Ranjana Dwivedi, Divyanshu Awasthi, and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Priyank Khare, Divyanshu Awasthi, and Vinay Kumar Srivastava
IEEE
Cultural images (CI) are the basis of our important heritage sites present on this earth. CI symbolic highlights for the culture and tradition which our society inherent it. Since the dissemination of CI is growing at a vital pace so their integrity needs to be protected from unauthorized users. In this proposed technique a novel image watermarking technique is designed for copyright protection of CI. Initially in this approach a hybrid watermark image is generated using CI and its geographical location with the aid of lifting wavelet transform (LWT), singular value decomposition (SVD), secure hash algorithm (SHA-384). The watermarking is performed out in YCbCr color domain using redundant discrete wavelet transform (RDWT), randomized singular value decomposition (RSVD) and fuzzy inference system (FIS) optimization technique. The role of FIS is to compute the value of embedding factor so that performance of proposed watermarking technique is strengthen. Several performance metrics are computed for the proposed technique which highlights for the efficiency as compared to other existing techniques.
Anurag Tiwari, Divyanshu Awasthi, and Vinay Kumar Srivastava
Elsevier
Divyanshu Awasthi, Priyank Khare, and Vinay Kumar Srivastava
CRC Press
Priyank Khare, Divyanshu Awasthi, and Vinay Kumar Srivastava
CRC Press
Ranjana Dwivedi, Divyanshu Awasthi, and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi, Priyank Khare, and Vinay Kumar Srivastava
SPIE-Intl Soc Optical Eng
Abstract. A transform domain digital image watermarking technique is proposed using bacterial foraging optimization (BFO) for telemedicine applications. To make a trade-off between robustness, imperceptibility, and authenticity is a significant focus of our work. The field of telemedicine is one of the critical areas for an intruder to make unwanted changes. The size of medical data is exponentially increasing since the pandemic. So, the security of medical data is also a big concern. One of the most important techniques to safeguard medical data is image watermarking. The digital imaging and communications in medical images of liver ultrasound are taken as input host images. Peak signal-to-noise ratio, Kullback–Leibler distance, and root-mean-square difference are used for BFO. The proposed BacterialWmark technique shows a significant improvement in robustness and imperceptibility compared with other existing techniques. The computational complexity of the proposed work is also less. The authentication of the watermarked image is successfully executed as the features are perfectly matched with the aid of the MinEigen algorithm. So, the BacterialWmark algorithm can be used in the field of telemedicine efficiently.
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Anurag Tiwari, Divyanshu Awasthi, and Vinay Kumar Srivastava
IEEE
The electrocardiogram (ECG) signal, which can be used to diagnose cardiovascular disorders, is one of the most significant segment of medical data. The sharing of digitized patient records across open networks has multiplied with the growth of point of care services. The smart healthcare facilities provide remote medical support using this digital data. The issue of encrypting this data during transmission is enormous. In the proposed work, Integer wavelet transform (IWT) and two-level decomposition-based scheme is utilized to embed multiple watermark (i) Patient information (ii) Fingerprint of patient. The 2-D ECG image is decomposed using 2 level IWT into different sub-bands. In the LL sub-band patient information (Pat-info) watermark image is embedded and into HH sub-band fingerprint of patient is embedded. The proposed method offers more than 70 dB PSNR value and NCC equal to 1.0000 under zero attack.
Divyanshu Awasthi, Priyank Khare, and Vinay Kymar Srivastava
IEEE
The size of the medical records (MR) is rising drastically after the pandemic era. The security, integrity and authenticity of MR is the need of an hour. In this work, YCbCr color space-based watermarking technique is proposed by using the properties of redundant discrete wavelet transform (RDWT), Schur decomposition (SD) and randomized singular value decomposition (RSVD). Hybrid watermark is generated by combining the Aadhar card of patient with the hash value (SHA-384) generated by taking Aadhar number as a string by using lifting wavelet transform (LWT) and singular value decomposition (SVD). Liver ultrasound and fundus images are taken as the host image. Binary robust invariant scalable keypoints (BRISK) are used to authenticate the features of watermarked images. To evaluate the performance of the proposed technique Average Peak signal to noise ratio (APSNR), Mean square error (MSE), Normalized correlation coefficient (NCC), Kullback-Leibler (KLD) and Jensen-Shannon (JSD) distances are calculated. By comparing the results with other existing schemes, it is clear that the proposed scheme is superior and can be used for securing the integrity and provide authenticity to MR.
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Nature Singapore
Divyanshu Awasthi, Priyank Khare, and Vinay Kumar Srivastava
IEEE
In this proposed work, YCbCr color space is used for watermarking. Three different watermark logos are used to watermark Y, Cb, and Cr color spaces. The proposed watermarking method uses fundus image, ultrasound DICOM (Digital Imaging and Communications in Medicine) image of liver and Lena image as the host images. This work uses the properties of Lifting wavelet transform (LWT), Discrete cosine transform (DCT), Schur decomposition and Singular value decomposition for watermarking. The LWT is used to split the image into different sub-bands (low-low, high-low, low-high, high-high). For watermarking HL, LH, and HH sub-bands are used. The SVD is used to extract the dominant matrix. The proposed scheme is highly robust and imperceptible when compared with other techniques. Speeded up robust features (SURF) are used for feature matching authentication. The presented scheme is resistant to numerous attacks, including Median filter, Salt and Pepper noise, Gaussian noise, Rotation, Average filter, Sharpening, Histogram equalization and Speckle noise. The Structural similarity index measurement (SSIM), Peak signal to noise ratio (PSNR), Normalized correlation coefficient (NCC), and mean square error (MSE) are the metrics that are used to evaluate the effectiveness of the proposed scheme.
Divyanshu Awasthi and Vinay Kumar Srivastava
Springer Science and Business Media LLC
Divyanshu Awasthi and Vinay Kumar Srivastava
IEEE
A dual-image watermarking approach is presented in this research. The presented work utilizes the properties of Hessenberg decomposition, Redundant discrete wavelet transform (RDWT), Discrete cosine transform (DCT) and Singular value decomposition (SVD). For watermarking, the YCbCr color space is employed. Two watermark logos are for embedding. A YCbCr format conversion is performed on the RGB input image. The host image's Y and Cb components are divided into various sub-bands using RDWT. The Hessenberg decomposition is applied on high-low and low-high components. After that, SVD is applied to get dominant matrices. Two different logos are used for watermarking. Apply RDWT on both watermark images. After that, apply DCT and SVD to get dominant matrices of logos. Add dominant matrices of input host and watermark images to get the watermarked image. Average PSNR, MSE, Structural similarity index measurement (SSIM) and Normalized correlation coefficient (NCC) are used as the performance parameters. The resilience of the presented work is tested against various attacks such as Gaussian low pass filter, Speckle noise attack, Salt and Pepper, Gaussian noise, Rotation, Median and Average filter, Sharpening, Histogram equalization and JPEG compression. The presented scheme is robust and imperceptible when compared with other schemes.