scholarly journals Quality Factor terhadap Kapasitas Pesan Rahasia pada Steganografi Citra JPEG dan Kualitas Citra Stego

2020 ◽  
Vol 6 (2) ◽  
pp. 89-100
Author(s):  
Dian Hafidh Zulfikar
Keyword(s):  
Image Quality ◽  
Quality Factor ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Secret Message ◽  
Q Factor ◽  
Stego Image ◽  
Jpeg Image ◽  
Human Eye

One of the container media that is available and popular is the Joint Photographic Experts Group (JPEG) format image. This article aims to determine the effect of Quality Factor on the secret message capacity of JPEG image steganography and stego image quality. The quality of an image can actually be seen subjectively with the human eye, but this is relative between each individual. Because the assessment of the human eye varies from person to person. In addition, the effect of Quality Factor on secret message capacity is not yet known whether it has an impact. Therefore, in this study the Quality Factor is used to objectively see the secret message capacity of the JPEG image steganography and the quality of the stego image. The parameter used to determine the quality of an image is the Peak Signal to Noise Ratio (PSNR). PSNR will compare the quality of the original image (before steganography) with the stego image. The test results show that the Q Factor effect can affect the secret message capacity of the JPEG image steganography and the stego image quality. The bigger the Q Factor, the more the message capacity is generated. The greater the Q factor, the better the quality of the resulting stego image.

Multilevel Secure Digital Image Steganography Framework Using Random Function and Advanced Encryption Standard

2019 ◽  
Vol 16 (11) ◽  
pp. 4812-4825
Author(s):  
Mohsin N. Srayyih Almaliki
Keyword(s):  
Image Quality ◽  
Random Function ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Secret Message ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Stego Image ◽  
Preparation Phase ◽  
Noise Ratio

One of the crucial aspects of processes and methodologies in the information and communication technology era is the security of information. The security of information should be a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies which are used, and they include steganography and cryptography. With cryptography, the secret message is converted into unintelligible text, but the existence of the secret message is noticed, nonetheless, steganography involves hiding the secret message in a way that its presence cannot be noticed. In this paper, a new secure image steganography framework which is known as an adaptive stego key LSB (ASK-LSB) framework is proposed. The construction of the proposed framework was carried out in four phases with the aim of improving the data-hiding algorithm in cover images by using capacity, image quality, and security. To achieve this, the Peak Signal-to-Noise Ratio (PSNR) of the steganography framework was maintained. The four phases began with the image preparation phase, followed by the secret message preparation phase, embedding phase and finally extraction phase. The secure image steganography framework that is proposed in this study is based on a new adaptive of least significant bit substitution method, combination random function, and encryption method. In the proposed work, the secret bits are inserted directly or inversely, thereby enhancing the imperceptibility and complexity of the process of embedding. Results from the experiment reveal that the algorithm has better image quality index, peak signal-to-noise ratio, and payload used in the evaluation of the stego image.

Reversible data hiding method based on pixel expansion and homomorphic encryption

2020 ◽  
Vol 39 (3) ◽  
pp. 2977-2990
Author(s):  
R. Anushiadevi ◽  
Padmapriya Praveenkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Homomorphic Encryption ◽  
Secret Message ◽  
Pixel Expansion ◽  
Stego Image ◽  
Encrypted Image ◽  
Location Map

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images.

scholarly journals Secure Image Steganography Algorithm Based on DCT with OTP Encryption

2017 ◽  
Vol 2 (1) ◽  
pp. 1-11 ◽  
Author(s):  
De Rosal Ignatius Moses Setiadi ◽  
Eko Hari Rachmawanto ◽  
Christy Atika Sari
Keyword(s):  
Discrete Cosine Transform ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Rapid Development ◽  
Median Filter ◽  
Image Steganography ◽  
Stego Image ◽  
Cosine Transform ◽  
The One

Rapid development of Internet makes transactions message even easier and faster. The main problem in the transactions message is security, especially if the message is private and secret. To secure these messages is usually done with steganography or cryptography. Steganography is a way to hide messages into other digital content such as images, video or audio so it does not seem nondescript from the outside. While cryptography is a technique to encrypt messages so that messages can not be read directly. In this paper have proposed combination of steganography using discrete cosine transform (DCT) and cryptography using the one-time pad or vernam cipher implemented on a digital image. The measurement method used to determine the quality of stego image is the peak signal to noise ratio (PSNR) and ormalize cross Correlation (NCC) to measure the quality of the extraction of the decrypted message. Of steganography and encryption methods proposed obtained satisfactory results with PSNR and NCC high and resistant to JPEG compression and median filter. Keywords—Image Steganography, Discrete Cosine Transform (DCT), One Time Pad, Vernam, Chiper, Image Cryptography

Secure Text Sharing Using Medical Image Steganography

2019 ◽  
Vol 7 (3) ◽  
pp. 37-43
Author(s):  
Boopathi. G et al.
Keyword(s):  
Digital Media ◽  
Signal To Noise Ratio ◽  
Data Communication ◽  
Image Steganography ◽  
Transform Domain ◽  
Stego Image ◽  
Secret Information ◽  
Multimedia Contents ◽  
Multiple Receivers

The increased popularity of digital media has raised serious concerns over its security related issues. Security attacks in the form of eavesdropping, masquerading and tampering and in many other forms is very common nowadays. Data hiding is one of the emerging techniques that aim to provide for security by hiding secret information into the multimedia contents by altering some nonessential components in the host or cover file. Security of data is very important in data communication. Everyday a lot of information is transferred from one user to another on internet and so the possibility of data theft also increases. Steganography provides a solution for the security of information during data transmission. Steganography is the science which makes the valuable information invisible to prevent it from unauthorized user. A steganography system, in general, is expected to meet three key requirements, namely, imperceptibility of embedding, accurate recovery of embedded information, and large payload (payload is the bits that get delivered to the end user at the destination). So in this project an image steganography technique is proposed to hide the documents in image in the transform domain using CMD approach. The document files are carried by the image without revealing the existence to anybody. When the secret information is hidden in the carrier the result is the stego signal. In this work, the results show good quality stego signal and the stego signal is analyzed for different attacks. The stego signals are transferred to multiple receivers based on network strategies. It is found that the technique is robust and it can withstand the attacks. The quality of the stego image is measured by Peak Signal to Noise Ratio (PSNR) and other measurements.

Secret Key-Based Image Steganography in Spatial Domain

2021 ◽  
pp. 2250014
Author(s):  
Rajashree Gajabe ◽  
Syed Taqi Ali
Keyword(s):  
Image Quality ◽  
Secure Communication ◽  
Image Steganography ◽  
Cover Image ◽  
Grayscale Image ◽  
Secret Key ◽  
Stego Image ◽  
Digital World ◽  
Day By Day

Day by day, the requirement for secure communication among users is rising in a digital world, to protect the message from the undesirable users. Steganography is a methodology that satisfies the user’s necessity of secure communication by inserting a message into different formats. This paper proposes a secret key-based image steganography to secure the message by concealing the grayscale image inside a cover image. The proposed technique shares the 20 characters long secret key between two clients where the initial eight characters of a secret key are utilized for bit permutation of characters and pixels while the last 12 characters of secret key decide the encryption keys and position of pixels of a grayscale image into the cover. The grayscale image undergoes operation such as encryption and chaotic baker followed by its hiding in a cover to form a stego image. The execution of the proposed strategy is performed on Matlab 2018. It shows that the proposed approach manages to store the maximum message of size 16[Formula: see text]KB into the cover of size [Formula: see text]. The image quality of stego images has been evaluated using PSNR, MSE. For a full payload of 16[Formula: see text]KB, PSNR is around 51[Formula: see text]dB to 53[Formula: see text]dB which is greater than satisfactory PSNR.

scholarly journals Authentic Data Transmission in Image with Different LSB Methods

2019 ◽  
Vol 8 (6) ◽  
pp. 4625-4628
Keyword(s):  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Third Party ◽  
Secret Message ◽  
Secret Key ◽  
Secret Data ◽  
Stego Image ◽  
Audio Data ◽  
Carrier Image ◽  
Authentic Data

A technique to hide undisclosed information from third party as well, the method of investigation to conceal secret data into the cover frame like text, audio, image and video without any change in substantial results to the carrier image is nothing but Steganography. The contemporary safe and taut steganography of image represents an exigent form of transformation of the inserted secrecy for the receiver with getting undetected [1-5]. In Image steganography, image is the carrier and any secret message (audio or text or image) can be transmitted. This algorithm of LSB can be executed in embedding territory where the secret audio data is inserted into the LSB of envelope image for creating the stego image. This paper gives the hiding of audio data as secret data in an image file using LSB with secret key and an improved inverted LSB image Steganography with improved mean square error and peak signal to noise ratio.

scholarly journals Hybrid Image Steganography Method Using LZW and Genetic Algorithm for Hiding Confidential Data

2020 ◽  
Author(s):  
Abdulkarem Almawgani ◽  
Adam Alhawari ◽  
Wlaed Alarashi ◽  
Ali Alshwal
Keyword(s):  
Genetic Algorithm ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Message ◽  
Adjustment Process ◽  
Discrete Wavelet ◽  
Secret Data ◽  
Stego Image ◽  
Lzw Algorithm

Abstract Digital images are commonly used in steganography due to the popularity of digital image transfer and exchange through the Internet. However, the tradeoff between managing high capacity of secret data and ensuring high security and quality of stego image is a major challenge. In this paper, a hybrid steganography method based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm, Genetic Algorithm (GA), and the Optimal Pixel Adjustment Process (OPAP) is proposed. The cover image is divided into non-overlapping blocks of nxn pixels. Then, the HDWT is used to increase the robustness of the stego image against attacks. In order to increase the capacity for, and security of, the hidden image, the LZW algorithm is applied on the secret message. After that, the GA is employed to give the encoded and compressed secret message cover image coefficients. The GA is used to find the optimal mapping function for each block in the image. Lastly, the OPAP is applied to reduce the error, i.e., the difference between the cover image blocks and the stego image blocks. This step is a further improvement to the stego image quality. The proposed method was evaluated using four standard images as covers and three types of secret messages. The results demonstrate higher visual quality of the stego image with a large size of embedded secret data than what is generated by already-known techniques. The experimental results show that the information-hiding capacity of the proposed method reached to 50% with high PSNR (52.83 dB). Thus, the herein proposed hybrid image steganography method improves the quality of the stego image over those of the state-of-the-art methods.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

The Influence of Alteration of kVp and mAs towards the Image Quality of Acrylic Using CBCT

2019 ◽  
Vol 829 ◽  
pp. 252-257
Author(s):  
Azhari ◽  
Yohanes Hutasoit ◽  
Freddy Haryanto
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Region Of Interest ◽  
Signal To Noise ◽  
Bite Block ◽  
Significant Difference ◽  
Noise Ratio ◽  
Post Hoc ◽  
Radiograph Image

CBCT is a modernized technology in producing radiograph image on dentistry. The image quality excellence is very important for clinicians to interpret the image, so the result of diagnosis produced becoming more accurate, appropriate, thus minimizing the working time. This research was aimed to assess the image quality using the blank acrylic phantom polymethylmethacrylate (PMMA) (C­5H8O2)n in the density of 1.185 g/cm3 for evaluating the homogeneity and uniformity of the image produced. Acrylic phantom was supported with a tripod and laid down on the chin rest of the CBCT device, then the phantom was fixed, and the edge of the phantom was touched by the bite block. Furthermore, the exposure of the X-ray was executed toward the acrylic phantom with various kVp and mAs, from 80 until 90, with the range of 5 kV and the variation of mA was 3, 5, and 7 mA respectively. The time exposure was kept constant for 25 seconds. The samples were taken from CBCT acrylic images, then as much as 5 ROIs (Region of Interest) was chosen to be analyzed. The ROIs determination was analyzed by using the ImageJ® software for recognizing the influence of kVp and mAs towards the image uniformity, noise and SNR. The lowest kVp and mAs had the result of uniformity value, homogeneity and signal to noise ratio of 11.22; 40.35; and 5.96 respectively. Meanwhile, the highest kVp and mAs had uniformity value, homogeneity and signal to noise ratio of 16.96; 26.20; and 5.95 respectively. There were significant differences between the image uniformity and homogeneity on the lowest kVp and mAs compared to the highest kVp and mAs, as analyzed with the ANOVA statistics analysis continued with the t-student post-hoc test with α = 0.05. However, there was no significant difference in SNR as analyzed with the ANOVA statistic analysis. The usage of the higher kVp and mAs caused the improvement of the image homogeneity and uniformity compared to the lower kVp and mAs.

Image quality of the human eye for eccentric entrance pupils

1983 ◽  
Vol 23 (5) ◽  
pp. 573-579 ◽  
Author(s):  
A. Van Meeteren ◽  
C.J.W. Dunnewold
Keyword(s):  
Image Quality ◽  
Human Eye
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