scholarly journals An efficient data hiding method in images

2019 ◽  
Vol 9 (6) ◽  
pp. 4713
Author(s):  
Saranya G
Keyword(s):  
Data Hiding ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Clinical Information ◽  
Contourlet Transform ◽  
Compression Method ◽  
Hiding Capacity ◽  
Space Saving ◽  
Efficient Data ◽  
And Storage

<p class="Abstract">Data Hiding has a huge range of applications in the medical field for transmission. It is helpful in securing the documentation of the patients from the violator with good storage space. The medical images of different modalities like CT, MRI, and PET with the digitized clinical information can be sent to the doctors across the world for the treatment. Due to the bandwidth and storage constraints, medical images along with the clinical information must be compressed before transmission and storage. This paper gives a technique for hiding the digitized clinical information along with the DICOM images in Complex Contourlet Transform (CCT) Domain. It also analyses the compression method by using an Entropy Encoder method. Hence, this work suggests that the data hiding method based on Complex Contourlet Transform (CCT) is efficient and also it has a high hiding capacity. The improved value of Compression Ratio (CR), Space Saving (SS), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) shows that the new method satisfies the properties of the data hiding method.</p>

Medical Image Reliability Verification Using Hash Signatures and Sequential Square Encoding

2018 ◽  
Vol 27 (1) ◽  
pp. 19-30
Author(s):  
J. Jennifer Ranjani ◽  
M. Babu
Keyword(s):  
Data Hiding ◽  
Medical Image ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Random Sequence ◽  
Region Of Interest ◽  
Critical Issue ◽  
Hiding Capacity ◽  
Random Sequence Generation ◽  
Image Integrity

Abstract Increased growth of information technology in healthcare has led to a situation where the security of patient information is more important and is a critical issue. The aim of the proposed algorithm is to provide a framework to verify the integrity of the medical images. In this paper, the integrity of the medical images is verified by embedding hash signatures using the sequential square embedding technique. This technique is as efficient as the diamond encoding technique but with increased payload capability. The medical image is first divided into the region of interest (ROI) block and the signature block. The hash signatures are determined by dividing the ROI into nonoverlapping blocks. During the data hiding stage, the hash signatures are embedded in randomly chosen pixel pairs in the signature block using the sequential square encoding (SSE) technique. In the experimental results, the data hiding capacity of the proposed SSE technique is verified in terms of peak signal-to-noise ratio. Also, the medical image integrity is substantiated by comparing the L2 norm between computed and extracted hash signatures. Modifications such as contrast enhancement, rotation, scaling, and changing the image information result in increased L2 norm; thus, the integrity of the medical images can be verified. The parameters required for embedding, such as the embedding parameter and the seed for random sequence generation, are encrypted and communicated to the receiving end. Hence, the proposed algorithm provides a secure framework for medical image integrity verification.

scholarly journals A Cryptographic based Approach for Data Hiding in Advanced Video Sequences

2021 ◽  
Vol 12 (6) ◽  
pp. 2031-2038
Author(s):  
Vinay D R, Dr. Anand Babu J
Keyword(s):  
Data Hiding ◽  
Signal To Noise Ratio ◽  
Video Quality ◽  
Similarity Index ◽  
Data Communication ◽  
Structural Similarity ◽  
Video Stream ◽  
Video Sequences ◽  
Video Streams ◽  
Hiding Capacity

Data hiding in video streams became more popular in the present world, since there is a high frequency of data communication over the internet. Hiding the data in video streams provides more security as well as increases embedding capacity than hiding inside the images. The quantity of information to be embedded into the video increases, it can badly influence the video excellence make it inappropriate for certain appliances. The main concerns in data hiding in videos are its high visual excellence, increased hiding capacity, video stream size etc. In this paper, a new data hiding technique is proposed in compressed H.264 Video Streams. At first, the information to be embedded is encrypted using Cryptography approach. The Cryptographic approach helps to encrypt the plain information based on the elliptic points produced by choosing the large prime number. The encrypted data is embedded into the transformed DCT coefficients of I, B and P video frames. The experiment is conducted for different set of video sequences. The results shows that the proposed method yields better performance in terms of Peak signal to noise ratio (PSNR), Structural similarity index (SSIM) and Video quality measure (VQM) when compare to existing methods.

scholarly journals Two-Bit Embedding Histogram-Prediction-Error Based Reversible Data Hiding for Medical Images with Smooth Area

Computers ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 152
Author(s):  
Ching-Yu Yang ◽  
Ja-Ling Wu
Keyword(s):  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Medical Images ◽  
High Capacity ◽  
Personal Privacy ◽  
Hiding Capacity ◽  
X Ray ◽  
Magnetic Resonance Imaging Mri ◽  
Hidden Data

During medical treatment, personal privacy is involved and must be protected. Healthcare institutions have to keep medical images or health information secret unless they have permission from the data owner to disclose them. Reversible data hiding (RDH) is a technique that embeds metadata into an image and can be recovered without any distortion after the hidden data have been extracted. This work aims to develop a fully reversible two-bit embedding RDH algorithm with a large hiding capacity for medical images. Medical images can be partitioned into regions of interest (ROI) and regions of noninterest (RONI). ROI is informative with semantic meanings essential for clinical applications and diagnosis and cannot tolerate subtle changes. Therefore, we utilize histogram shifting and prediction error to embed metadata into RONI. In addition, our embedding algorithm minimizes the side effect to ROI as much as possible. To verify the effectiveness of the proposed approach, we benchmarked three types of medical images in DICOM format, namely X-ray photography (X-ray), computer tomography (CT), and magnetic resonance imaging (MRI). Experimental results show that most of the hidden data have been embedded in RONI, and the performance achieves high capacity and leaves less visible distortion to ROIs.

scholarly journals Reversible difference expansion multi-layer data hiding technique for medical images

2021 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Pascal Maniriho ◽  
Leki Jovial Mahoro ◽  
Zephanie Bizimana ◽  
Ephrem Niyigaba ◽  
Tohari Ahmad
Keyword(s):  
Data Hiding ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Data Communication ◽  
Low Complexity ◽  
Difference Expansion ◽  
Stego Image ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Private Data

Maintaining the privacy and security of confidential information in data communication has always been a major concern. It is because the advancement of information technology is likely to be followed by an increase in cybercrime, such as illegal access to sensitive data. Several techniques were proposed to overcome that issue, for example, by hiding data in digital images. Reversible data hiding is an excellent approach for concealing private data due to its ability to be applied in various fields. However, it yields a limited payload and the quality of the image holding data (Stego image), and consequently, these two factors may not be addressed simultaneously. This paper addresses this problem by introducing a new non-complexity difference expansion (DE) and block-based reversible multi-layer data hiding technique constructed by exploring DE. Sensitive data are embedded into the difference values calculated between the original pixels in each block with relatively low complexity. To improve the payload capacity, confidential data are embedded in multiple layers of grayscale medical images while preserving their quality. The experiment results prove that the proposed technique has increased the payload with an average of 369999 bits and kept the peak signal to noise ratio (PSNR) to the average of 36.506 dB using medical images' adequate security the embedded private data. This proposed method has improved the performance, especially the secret size, without reducing much the quality. Therefore, it is suitable to use for relatively big payloads.

scholarly journals Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed

2019 ◽  
Vol 8 (4) ◽  
pp. 11473-11478
Keyword(s):  
Data Hiding ◽  
Enhanced Recovery ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Cover Image ◽  
Mapping Technique ◽  
Secret Data ◽  
Logical Function ◽  
Hiding Capacity ◽  
Carrier Image

In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.

scholarly journals A Robust Image Watermarking Method based on Contourlet Transform for Correcting Geometric Attacks

2018 ◽  
Vol 7 (2.24) ◽  
pp. 24
Author(s):  
Abhinaya M ◽  
A Umamakeswari
Keyword(s):  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Random Sequence ◽  
Mapping Function ◽  
Contourlet Transform ◽  
Discrete Wavelet ◽  
Hiding Capacity ◽  
Geometric Attacks ◽  
Affine Translation ◽  
Value Decomposition

A watermarking technique is proposed using Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Singular Value Decomposition (SVD) techniques to implement information hiding. Embedding can be done by dividing the host image into four rectangular segments which are non-overlapping called sub-images using hybrid scheme. Redundancy reduces cropping attack. The main aim is to reduce the effect of geometric bouts, such as rotation, translation, and affine translation using synchronization technique. Watermarks can be a binary random sequence of different lengths. Data replication and hamming code are two error modification methods utilized in the proposed scheme. Achieved results show comparable robustness against geometric attacks and signal processing. Contourlet transform can be used to improve the visual feature of the image. After embedding the image or data, contourlet transform is applied in the frequency domain to improve robustness. The optimal mapping function is obtained using contourlet transform which increases Peak Signal to Noise Ratio (PSNR) and hiding capacity with low distortion.  

scholarly journals Authenticated Medical Image Transmission using Enhanced Reversible Data Hiding (RDH) with NNP2 Algorithm and Rhombus Prediction

2019 ◽  
Vol 8 (4) ◽  
pp. 12188-12192
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Medical Information ◽  
Medical Images ◽  
Chinese Remainder Theorem ◽  
Image Transmission ◽  
Hiding Capacity ◽  
Distortion Level ◽  
Home Monitor ◽  
Nearest Neighborhood

During the last few years, the medical information of concerned patient is transferred from one doctor to another doctor via internet for better diagnosis and studies. Transferring medical information over a transmission medium is known as telemedicine. Telemedicine has been used to overcome distance barriers and to improve access to medical service. The telemedicine application includes emergency treatment, home monitor, military applications, and medical education. These medical images are corrupted by hackers when it is transferred through internet. Hence security of medical images is necessary. Watermarking is used for providing security while transferring medical images. Reversible Data Hiding (RDH) is one of the efficient methods for secure transmission of medical images. In this method, data hiding capacity is very small and the distortion level of recovers images is very large. To avoid these drawbacks, Nearest Neighborhood Pixel Prediction (NNP2 ) algorithm based on Chinese Remainder Theorem (CRT) is proposed and Rhombus Prediction is applied in NNP2 to increase data hiding capacity. The distortion level is reduced by Histogram Shifting. The performance of proposed method is evaluated using PSNR for number of medical images. The results shows that the proposed method gives good results when compared with traditional methods.

scholarly journals Reversible Data Hiding in Encrypted Image Based on (7, 4) Hamming Code and UnitSmooth Detection

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 790
Author(s):  
Lin Li ◽  
Chin-Chen Chang ◽  
Chia-Chen Lin
Keyword(s):  
Data Hiding ◽  
Privacy Protection ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Data Extraction ◽  
Hamming Code ◽  
Hiding Capacity ◽  
Encrypted Images

With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) plays the dual role of privacy protection and secret information transmission. RDHEI has a good application prospect and practical value. The current RDHEI algorithms still have room for improvement in terms of hiding capacity, security and separability. Based on (7, 4) Hamming Code and our proposed prediction/ detection functions, this paper proposes a Hamming Code and UnitSmooth detection based RDHEI scheme, called HUD-RDHEI scheme for short. To prove our performance, two database sets—BOWS-2 and BOSSBase—have been used in the experiments, and peak signal to noise ratio (PSNR) and pure embedding rate (ER) are served as criteria to evaluate the performance on image quality and hiding capacity. Experimental results confirm that the average pure ER with our proposed scheme is up to 2.556 bpp and 2.530 bpp under BOSSBase and BOWS-2, respectively. At the same time, security and separability is guaranteed. Moreover, there are no incorrect extracted bits during data extraction phase and the visual quality of directly decrypted image is exactly the same as the cover image.

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