scholarly journals Innovative Region Based Steganographic Technique to Provide Security and Authentication to Digital Image

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3706-3710
Keyword(s):  
Mean Square Error ◽  
Digital Image ◽  
Image Steganography ◽  
The Internet ◽  
Main Concern ◽  
Mean Square ◽  
Least Significant Bit ◽  
Lsb Technique ◽  
Intended Receiver

In this advanced world with the growing technology, the demand for security of information is needed in any communication streams of data which is being conveyance from host to intended host over the internet. Obviously, a huge & numerous amount of the data or the information are transferred in our everyday. So, the demand for securing information has become the main concern. Image Steganography is one of the important areas in the field of Steganography. The main purpose of steganography is to protect the surreptitious information from others except from intended receiver & by increasing the security of the covert data in the significant way that information can’t be revealed although the intruder knows the methodology of the embedding process. In this paper, The aim is to propose a different yet, an innovative steganographical technique which provides the security on our digital image, and by using a quality measuring technique like Mean Square Error(MSE), Peak Signal Noise Ratio (PSNR) which assure the quality of image has been not degraded even after infusing the covert data inside the image. So to overcome these issues, this paper, suggests a new method to maintain the quality of the image. After embedding the authenticated information in the cover image using Region-Based Least Significant Bit (LSB) technique that provides security of digital image

scholarly journals Implementasi Steganografi Video dengan Menggunakan Metode Egypt, Least Significant Bit (LSB) dan Least Significant Bit (LSB) Fibonacci Edge Pixel

2020 ◽  
Vol 10 (1) ◽  
pp. 25
Author(s):  
Ranida Pradita ◽  
Ida Nurhaida
Keyword(s):  
Mean Square Error ◽  
Digital Image ◽  
Digital Video ◽  
3D Model ◽  
Signal To Noise Ratio ◽  
Mean Square ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Edge Pixel ◽  
Audio Video

Seiring dengan perkembangan teknologi 5G, penyebaran dengan menggunakan video semakin besar dan mudah. Penyebaran informasi baik yang tersembunyi atau tidak semakin mudah disebarluaskan dengan menggunakan internet. Steganografi adalah cara menyembunyikan informasi dalam image atau video. Steganografi berbentuk digital image, text, audio, video, 3D model, dan lain-lain. Media digital yang popularitasnya paling tinggi dalam penelitian algoritma steganografi dengan menggunakan media digital image. Tulisan ini menggunakan media digital video karna media penelitian sebelumnya menggunakan media digital image. Pada tulisan ini akan diulas dan dianalis tentang video steganografi dengan menggunakan metode Egypt, Least Significant Bit (LSB), dan Least Significant Bit (LSB) Fibonacci Edge Pixel. Analisis video steganografi ini bertujuan untuk mendeteksi video yang mengandung unsur pesan rahasia yang kemungkinan untuk pengintaian. Hasil Peak Signal-to-Noise Ratio (PSNR) yang didapat dari penelitian ini rata-rata 40.46 dB dan menghasilkan rata-rata presentase similarity 30.67 %. Rata-rata Mean Square Error (MSE) pada penelitian ini adalah sebesar 0.50657. Untuk metode yang paling optimal yang digunakan dalam video steganografi adalah dengan menggunakan Metode Egypt.

scholarly journals Steganographic Techniques Using Modified Least Significant Bit and Modification Reshape Transposition Methods

2021 ◽  
Vol 13 (1) ◽  
pp. 67-77
Author(s):  
Guntoro Barovih ◽  
Fadhila Tangguh Admojo ◽  
Yoda Hersaputra
Keyword(s):  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Lossless Compression ◽  
Mean Square ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Image File ◽  
Modification Technique ◽  
Noise Ratio

A message is a form of conveying information. Various ways are used to secure the information conveyed in the form of messages either in encrypted form or in the form of applying a password in the message. Messages can also be encrypted and embedded in other media such as images (steganography). This research aimed to insert a message into the form of an image by combining the Modified Least Significant Bit (MLSB) method in encrypting messages and reshape modification technique to determine at which position the message encryption will be embedded in the image. Tests were carried out to obtain the quality of the encryption process using the parameters of Fidelity, mean square error, peak signal to noise ratio, testing on file type, robustness, and comparison of message contents. The results of the tests showed that the files that can be used are files with the image file type in the lossless compression category, the rotation can be done at 90, 180, 270 without destroying the message in it, and changing the pixel in the image file will destroy the message inside

scholarly journals Image Steganography using LSB and encrypted message with AES, RSA, DES, 3DES, and Blowfish

2019 ◽  
Vol 8 (6S3) ◽  
pp. 204-208
Keyword(s):  
Mean Square Error ◽  
Execution Time ◽  
Signal To Noise Ratio ◽  
Digital Data ◽  
Mean Square ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Stego Image ◽  
Cryptographic Algorithms

In today’s world, confidential information is growing due to various areas of works. Internet is the main area of transmission of digital data, so security must be more considered. Two common ways of providing security is cryptography and steganography. Employing a hybrid of cryptography and steganography enhances the security of data. This paper employs LSB (Least significant Bit) as the steganography algorithm and AES, RSA, DES, 3DES, and Blowfish algorithms as cryptographic algorithms to encrypt a message that should be hidden in a cover image. The results are represented in the form of execution time, PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error) and the histogram of main and covered image. The experimental results reveal that all the algorithms achieve appropriate quality of stego image. They can be used as cryptographic algorithms to encrypt a message before applying steganography algorithms.

scholarly journals Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter

2020 ◽  
Vol 30 (1) ◽  
pp. 240-257
Author(s):  
Akula Suneetha ◽  
E. Srinivasa Reddy
Keyword(s):  
Image Quality ◽  
Mean Square Error ◽  
Fuzzy Set ◽  
Digital Image ◽  
Gaussian Noise ◽  
Digital Images ◽  
Structural Similarity ◽  
Fuzzy Rules ◽  
Mean Square ◽  
Image Edges

Abstract In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques.

scholarly journals Quality of wood in the stands of poplar clones

2008 ◽  
Vol 54 (No. 1) ◽  
pp. 9-16
Author(s):  
R. Petráš ◽  
J. Mecko ◽  
V. Nociar
Keyword(s):  
Root Mean Square Error ◽  
Systematic Error ◽  
Mean Square Error ◽  
Statistical Tests ◽  
Mean Square ◽  
Poplar Clones ◽  
Mean Diameter ◽  
Empirical Material ◽  
Relative Root

The results obtained in research on the quality of raw timber by means of the structure of assortments for the stands of poplar clones Robusta and I-214 are presented in the paper. Models for an estimation of the structure of basic assortments of poplar stands were constructed separately for each clone in dependence on mean diameter, quality of stems, and damage to stems in the stand. The clone Robusta has higher proportions of higher-quality assortments than the clone I-214. The accuracy of models was determined on empirical material. It was confirmed by statistical tests that the models did not have a systematic error. The relative root mean-square error for main assortments of the clone I-214 is 15–27% and Robusta 13–24%.

Comparison of Thresholding and Edge Detection Segmentation Techniques

2013 ◽  
Vol 860-863 ◽  
pp. 2783-2786
Author(s):  
Yu Bing Dong ◽  
Hai Yan Wang ◽  
Ming Jing Li
Keyword(s):  
Image Segmentation ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Experimental Results ◽  
Mean Square ◽  
Segmentation Method ◽  
Segmentation Algorithms

Edge detection and thresholding segmentation algorithms are presented and tested with variety of grayscale images in different fields. In order to analyze and evaluate the quality of image segmentation, Root Mean Square Error is used. The smaller error value is, the better image segmentation effect is. The experimental results show that a segmentation method is not suitable for all images segmentation.

scholarly journals An Image Steganography Algorithm using Fractional Discrete Wavelet Transform with Advanced Encryption System

2020 ◽  
Vol 9 (5) ◽  
pp. 541-546
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

The research constitutes a distinctive technique of steganography of image. The procedure used for the study is Fractional Random Wavelet Transform (FRWT). The contrast between wavelet transform and the aforementioned FRWT is that it comprises of all the benefits and features of the wavelet transform but with additional highlights like randomness and partial fractional value put up into it. As a consequence of the fractional value and the randomness, the algorithm will give power and a rise in the surveillance layers for steganography. The stegano image will be acquired after administrating the algorithm which contains not only the coated image but also the concealed image. Despite the overlapping of two images, any diminution in the grade of the image is not perceived. Through this steganographic process, we endeavor for expansion in surveillance and magnitude as well. After running the algorithm, various variables like Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR) are deliberated. Through the intended algorithm, a rise in the power and imperceptibility is perceived and it can also support diverse modification such as scaling, translation and rotation with algorithms which previously prevailed. The irrefutable outcome demonstrated that the algorithm which is being suggested is indeed efficacious.

Improved Capacity Image Steganography Algorithm using 16-Pixel Differencing with n-bit LSB Substitution for RGB Images

2016 ◽  
Vol 6 (6) ◽  
pp. 2735 ◽  
Author(s):  
Meenakshi S Arya ◽  
Meenu Rani ◽  
Charndeep Singh Bedi
Keyword(s):  
Digital Media ◽  
Daily Basis ◽  
Image Steganography ◽  
The Internet ◽  
Least Significant Bit ◽  
Content Protection ◽  
Hiding Capacity ◽  
Pixel Value ◽  
Four Levels ◽  
Lsb Substitution

<p>With the intrusion of internet into the lives of every household and terabytes of data being transmitted over the internet on daily basis, the protection of content being transmitted over the internet has become an extremely serious concern. Various measures and methods are being researched and devised everyday to ensure content protection of digital media. To address this issue of content protection, this paper proposes an RGB image steganography based on sixteen-pixel differencing with n-bit Least Significant Bit (LSB) substitution. The proposed technique provides higher embedding capacity without sacrificing the imperceptibility of the host data. The image is divided into 4×4 non overlapping blocks and in each block the average difference value is calculated. Based on this value the block is classified to fall into one of four levels such as, lower, lower-middle, higher-middle and higher. If block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle and higher level blocks 3, 4, and 5 bit LSB substitution is used. In our proposed method there is no need of pixel value readjustment for minimizing distortion. The experimental results show that stego-images are imperceptible and have huge hiding capacity.</p>

Selecting velocity fields in urban pluvial floods from pre-calculated data

2020 ◽  
Author(s):  
Robert Sämann ◽  
Thomas Graf ◽  
Insa Neuweiler
Keyword(s):  
High Resolution ◽  
Water Level ◽  
Mean Square Error ◽  
Nearest Neighbor ◽  
Calculated Data ◽  
Velocity Fields ◽  
Water Levels ◽  
Mean Square ◽  
Run Off

&lt;p&gt;&lt;span&gt;Early warning systems for floods in urban areas should forecast water levels and damage estimation to protect vulnerable regions. To estimate the danger of a flood for buildings and people, the energy of the flood has to be taken into account additionally to the water level. The energy is related to the flow velocity. For directing rescue workers or trace spreading of contaminants through flooded streets, a high resolution of the water&amp;#8217;s energy in space and time is required. Direct numerical run-off calculation is too slow for a flood forecast in time. Therefore a database with pre-calculated events is needed and a method to select the water levels and velocity fields that are similar to a forecasted rain event. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;We present a method, how to create a real-time forecast based on pre-calculated data. The selection and weighting of the pre-calculated data is based on the precipitation pattern in the flood region. A nearest neighbor approach is applied to find water levels and velocity fields from a database that are similar to the forecasting event. For the ranking of similarity, different new metrics are compared against each other. The quality of the metrics is tested with a new approach of comparing velocity fields on the surface and in the pipe system. Considering both domains is crucial for understanding the complex dynamic flow paths on the surface. An urban catchment of 5&amp;#160;km&amp;#178; with high resolution (~3 m&amp;#179;) triangular surface mesh and connected drainage system is used for a hydrodynamic run-off simulation. The 1D-2D coupled software HYSTEM EXTRAN is used to generate the water levels and velocity fields for strong rainfall events of the past 20 years. More than 900 events with a duration between 15 minutes and 24&amp;#160;hours and return periods between 10 and 100 years were calculated and stored as the &amp;#8220;pre-calculated&amp;#8221; dataset.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;For comparing two events, the mean square error is calculated between the precipitation patterns with different approaches to select the start index and number of intervals. This number depends on the hydraulic response time, the temporal resolution and the length of the reference pattern. The quality of the nearest neighbor selection is quantified using the Nash&amp;#8211;Sutcliffe model efficiency coefficient of pipe flow and the root mean square error of water level and velocity in significant surface cells. Additionally, the transport paths of artificial contamination spills are compared between the events to show the reproducibility of velocity fields for each metric. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;Results show that the reaction time and the wetting state of the surface is very important. Single cell values correspond well between a forecasted and a dataset event. However, complex transport paths have a very high variability that is not reproducible with similar events. Further research is required to clarify if this is a result of the random walk approach or of the injection time of the particles. &lt;/span&gt;&lt;/p&gt;

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