Abstract
Digital images can be changed easily nowadays through the use of sophisticated software to edit images such as (Adobe Photoshop®). You can look at some manipulated pictures along the lines of the original images without any suspicion that they are also modified. Accordingly, the use of such software to edit the image makes ratification a difficult task and the use of this image in the courts for proving may become impossible.In this paper, a new method has been proposed for water fragile signs depending on the method of Pixel-wise. The proposed method is based on the included secret watermark and check bits in the green layer to the image of the colorful cover with the size of 512x512. The process of including watermark deals with the green class as a chess board with 512 x 512 sizes to avoid the inclusion of sequential bits in the spatial areas of the image of the cover. The process of extracting and discriminating the manipulation of watermark is used to determine whether the manipulation of the image containing watermark was done by an opponent or not. Therefore, the use of the extracted watermark and matrix manipulation to check the image containing watermark sent. Depending on the experimental results, the proposed method provides high quality, low distortion in the images contained watermark PSNR depending on their values. Also, the ability to recognize manipulation in the picture containing watermark in cases such as adding objects to the image containing the watermark, and the application of JPEG compression on image containing watermark, and removing objects from the image containing watermark, repeating the object image containing watermark, and adding a text on image including watermark.
Keywords: Check-bits, Fragile watermarking, PSNR, Secret watermark, Watermarked-image.
Performance Comparison of Digital Image Watermarking Techniques: A SurveyEditor IJCATR
Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image,
which is overlaid on the host image, and provides a means of protecting the image. In order to provide high quality watermarked
image, the watermarked image should be imperceptible. This paper presents different techniques of digital image watermarking based
on spatial & frequency domain, which shows that spatial domain technique provides security & successful recovery of watermark
image and higher PSNR value compared to frequency domain.
Abstract: A number of research papers has been produced about reversible watermarking. Reversible
watermarking is one of the important scheme of the watermarking schemes. Some security measures must be
there to protect the records from unauthorized user and destruction of information. Basic idea of digital
watermarking is to embed the data into the cover media to provide the security to data. The watermarking
techniques satisfying these requirements called as Reversible watermarking. Ownership of the original media
remains same but the best thing is original media is recovered from the watermarked media. This is the best and
main feature of reversible watermarking to extract the original image as it is without any distortion. This
feature is applicable in various areas such as medical as well as military images. If there is effect on the cover
then it would changes the meaning of this data. The aim of this paper is to represent the purpose of reversible
watermarking, some of the techniques related to reversible watermarking.
Keywords: Reversible watermarking, Security, copyright protection
THE EFFECT OF PHYSICAL BASED FEATURES FOR RECOGNITION OF RECAPTURED IMAGESijcsit
It is very simple and easier to recapture a high quality images from LCD screens with the development of multimedia technology and digital devices. In authentication, the use of such recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Even though, there are a number of features that have been proposed in various state-of-theart
visual recognition tasks, but it is still difficult to decide which feature or combination of features have more significant impact on this task. In this paper an image recapture detection method based on set of physical based features including texture, HSV colour and blurriness is proposed. Also, this paper evaluates the performance of different distinctive featuresin the context of recognition of recaptured
images. Several experimental setups have been conducted in order to demonstrate the performance of the proposed method. In all these experimental results, the proposed method is efficient with good recognition rate. Among the combination of low-level features, CS-LBP detection is to operator which is used to extract the texture feature is the most robust feature.
RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORKijaia
The complementary DNA (cDNA) sequence considered the magic biometric technique for personal identification. Microarray image processing used for the concurrent genes identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN). We have segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarray image resized and used as an input for the
proposed artificial neural network. For matching and recognition, we have trained the artificial neural
network. Recognition results are given for the galleries of cDNA sequences . The numerical results show
that, the proposed matching technique is an effective in the cDNA sequences process. The experimental
results of our matching approach using different databases shows that, the proposed technique is an effective matching performance.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
PREVENTING COPYRIGHTS INFRINGEMENT OF IMAGES BY WATERMARKING IN TRANSFORM DOM...ijistjournal
Images are undoubtedly the most efficacious and easiest means of communicating an idea. They are surely an indispensable part of human life .The trend of sharing images of various kinds for example typical technical figures, modern exceptional masterpiece from an artist, photos from the recent picnic to hill station etc, on the internet is spreading like a viral. There is a mandatory requirement for checking the privacy and security of our personal digital images before making them public via the internet. There is always a threat of our original images being illegally reproduced or distributed elsewhere. To prevent the misuse and protect the copyrights, an efficient solution has been given that can withstand many attacks. This paper aims at encoding of the host image prior to watermark embedding for enhancing the security. The fast and effective full counter propagation neural network helps in the successful watermark embedding without deteriorating the image perception. Earlier techniques embedded the watermark in the image itself but is has been observed that synapses of neural network provide a better platform for reducing the distortion and increasing the message capacity.
Human motion is fundamental to understanding behaviour. In spite of advancement on single image 3 Dimensional pose and estimation of shapes, current video-based state of the art methods unsuccessful to produce precise and motion of natural sequences due to inefficiency of ground-truth 3 Dimensional motion data for training. Recognition of Human action for programmed video surveillance applications is an interesting but forbidding task especially if the videos are captured in an unpleasant lighting environment. It is a Spatial-temporal feature-based correlation filter, for concurrent observation and identification of numerous human actions in a little-light environment. Estimated the presentation of a proposed filter with immense experimentation on night-time action datasets. Tentative results demonstrate the potency of the merging schemes for vigorous action recognition in a significantly low light environment.
Performance Comparison of Digital Image Watermarking Techniques: A SurveyEditor IJCATR
Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image,
which is overlaid on the host image, and provides a means of protecting the image. In order to provide high quality watermarked
image, the watermarked image should be imperceptible. This paper presents different techniques of digital image watermarking based
on spatial & frequency domain, which shows that spatial domain technique provides security & successful recovery of watermark
image and higher PSNR value compared to frequency domain.
Abstract: A number of research papers has been produced about reversible watermarking. Reversible
watermarking is one of the important scheme of the watermarking schemes. Some security measures must be
there to protect the records from unauthorized user and destruction of information. Basic idea of digital
watermarking is to embed the data into the cover media to provide the security to data. The watermarking
techniques satisfying these requirements called as Reversible watermarking. Ownership of the original media
remains same but the best thing is original media is recovered from the watermarked media. This is the best and
main feature of reversible watermarking to extract the original image as it is without any distortion. This
feature is applicable in various areas such as medical as well as military images. If there is effect on the cover
then it would changes the meaning of this data. The aim of this paper is to represent the purpose of reversible
watermarking, some of the techniques related to reversible watermarking.
Keywords: Reversible watermarking, Security, copyright protection
THE EFFECT OF PHYSICAL BASED FEATURES FOR RECOGNITION OF RECAPTURED IMAGESijcsit
It is very simple and easier to recapture a high quality images from LCD screens with the development of multimedia technology and digital devices. In authentication, the use of such recaptured images can be very dangerous. So, it is very important to recognize the recaptured images in order to increase authenticity. Even though, there are a number of features that have been proposed in various state-of-theart
visual recognition tasks, but it is still difficult to decide which feature or combination of features have more significant impact on this task. In this paper an image recapture detection method based on set of physical based features including texture, HSV colour and blurriness is proposed. Also, this paper evaluates the performance of different distinctive featuresin the context of recognition of recaptured
images. Several experimental setups have been conducted in order to demonstrate the performance of the proposed method. In all these experimental results, the proposed method is efficient with good recognition rate. Among the combination of low-level features, CS-LBP detection is to operator which is used to extract the texture feature is the most robust feature.
RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORKijaia
The complementary DNA (cDNA) sequence considered the magic biometric technique for personal identification. Microarray image processing used for the concurrent genes identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN). We have segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarray image resized and used as an input for the
proposed artificial neural network. For matching and recognition, we have trained the artificial neural
network. Recognition results are given for the galleries of cDNA sequences . The numerical results show
that, the proposed matching technique is an effective in the cDNA sequences process. The experimental
results of our matching approach using different databases shows that, the proposed technique is an effective matching performance.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
PREVENTING COPYRIGHTS INFRINGEMENT OF IMAGES BY WATERMARKING IN TRANSFORM DOM...ijistjournal
Images are undoubtedly the most efficacious and easiest means of communicating an idea. They are surely an indispensable part of human life .The trend of sharing images of various kinds for example typical technical figures, modern exceptional masterpiece from an artist, photos from the recent picnic to hill station etc, on the internet is spreading like a viral. There is a mandatory requirement for checking the privacy and security of our personal digital images before making them public via the internet. There is always a threat of our original images being illegally reproduced or distributed elsewhere. To prevent the misuse and protect the copyrights, an efficient solution has been given that can withstand many attacks. This paper aims at encoding of the host image prior to watermark embedding for enhancing the security. The fast and effective full counter propagation neural network helps in the successful watermark embedding without deteriorating the image perception. Earlier techniques embedded the watermark in the image itself but is has been observed that synapses of neural network provide a better platform for reducing the distortion and increasing the message capacity.
Human motion is fundamental to understanding behaviour. In spite of advancement on single image 3 Dimensional pose and estimation of shapes, current video-based state of the art methods unsuccessful to produce precise and motion of natural sequences due to inefficiency of ground-truth 3 Dimensional motion data for training. Recognition of Human action for programmed video surveillance applications is an interesting but forbidding task especially if the videos are captured in an unpleasant lighting environment. It is a Spatial-temporal feature-based correlation filter, for concurrent observation and identification of numerous human actions in a little-light environment. Estimated the presentation of a proposed filter with immense experimentation on night-time action datasets. Tentative results demonstrate the potency of the merging schemes for vigorous action recognition in a significantly low light environment.
An Experimental Study into Objective Quality Assessment of Watermarked ImagesCSCJournals
In this paper, we study the quality assessment of watermarked and attacked images using extensive experiments and related analysis. The process of watermarking usually leads to loss of visual quality and therefore it is crucial to estimate the extent of quality degradation and its perceived impact. To this end, we have analyzed the performance of 4 image quality assessment (IQA) metrics – Structural Similarity Index (SSIM), Singular Value Decomposition Metric (M-SVD) and Image Quality Score (IQS) and PSNR on watermarked and attacked images. The watermarked images are obtained by using three different schemes viz., (1) DCT based random number sequence watermarking, (2) DWT based random number sequence watermarking and (3) RBF Neural Network based watermarking. The signed images are attacked by using five different image processing operations. We observe that the metrics behave identically in case of all the three watermarking schemes. An important conclusion of our study is that PSNR is not a suitable metric for IQA as it does not correlate well with the human visual system’s (HVS) perception. It is also found that the M-SVD scatters significantly after embedding the watermark and after attacks as compared to SSIM and IQS. Therefore, it is a less effective quality assessment metric for watermarked and attacked images. In contrast to PSNR and M-SVD, SSIM and IQS exhibit more stable and consistent performance. Their comparison further reveals that except for the case of counterclockwise rotation, IQS relatively scatters less for all other four attacks used in this work. It is concluded that IQS is comparatively more suitable for quality assessment of signed and attacked images.
Automation systems, especially in the world of robotics, are becoming faster creating an increasing need to track objects at higher speeds than ever before.
Systems which rely on computer vision analysis to make artificial intelligence decisions and provide control, extend from high speed production lines and robot arms to autonomous guided vehicles, missiles and planes. Such systems use computer vision algorithms to extract information from images in a video sequence to identify and track objects in a scene. Usually these algorithms require high computational resources from a general purpose processor or a DSP, causing high computational latencies. High latencies act as a prohibitive factor for providing true, real time recognition and tracking of objects moving at high velocities.
Company Concurrent Vision ApS develops real time, high speed, vision-based systems that identify and track objects in a continuous video stream. These systems are based on the digital ASIC and FPGA technologies to implement high speed parallel computations providing true real time recognition and tracking of objects moving at speeds above 200 km/h. Typical applications of these systems include active video surveillance, vision- based robotic arms motion control, providing cognitive characteristics to robots and tracking high speed moving targets. Of other applications can be mentioned video stabilizing, augmented reality, image stitching, real time demosaicing for high definition video cameras, 3D imaging, intelligent toy and physical interactive computer games.
Concurrent Vision also provides solutions for the acceleration of high speed content based image retrieval systems that search for digital images in large databases. An example of such systems is retrieval and matching medical images for computer aided diagnosis.
Implementation of digital image watermarking techniques using dwt and dwt svd...eSAT Journals
Abstract
These days, in every field there is gigantic utilization of computerized substance. Data took care of on web and mixed media system framework is in advanced structure. Computerized watermarking is only the innovation in which there is inserting of different data in advanced substance, which we need to shield from illicit replicating. Computerized picture watermarking is concealing data in any structure (content, picture, sound and video) in unique picture without corrupting its perceptual quality. On the off chance that of Discrete Wavelet Transform (DWT), deterioration of the first picture is completed to insert the watermark. Moreover, if there should arise an occurrence of cross breed system (DWT-SVD) firstly picture is decayed by and after that watermark is installed in solitary qualities acquired by application of Singular Value Decomposition (SVD). DWT and SVD are utilized in combination to enhance the nature of watermarking. We have the procedures which are looked at on the premise of Peak Signal to Noise Ratio (PSNR) esteem at various benefits of scaling component; high estimation of PSNR is coveted because it displays great intangibility of the strategy.
Diabetic retinopathy also known as diabetic eye disease, is when damage occurs to the retina
due to diabetes. It can eventually lead to blindness. By analyzing and detecting vasculature structures
in retinal image the diabetes can be detected in advanced stages by comparing its states of retinal
blood vessels. In blood vessel classification approach computer based retinal image analysis can be
used to extract the retinal image vessels. Stationary wavelet transform (SWT) are used to extract the
features from the fundus image and classification can be performed using Support Vector
Machine(SVM). SVM has become an essential machine learning method for the detection and
classification of particular patterns in medical images. It is used in a wide range of applications for its
ability to detect patterns in experimental databases. If the vessels are present, then it is extracted by
using segmentation. Mathematical morphology and K-means clustering is used to segment the vessels.
To enhance the blood vessels and suppress the background information, smoothing operation can be
performed on the retinal image using mathematical morphology. Then the enhanced image is
segmented using K-means clustering algorithm to detect the diseases easily.
Reviewing the Effectivity Factor in Existing Techniques of Image Forensics IJECEIAES
Studies towards image forensics are about a decade old and various forms of research techniques have been presented till date towards image forgery detection. Majority of the existing techniques deals with identification of tampered regions using different forms of research methodologies. However, it is still an open-end question about the effectiveness of existing image forgery detection techniques as there is no reported benchmarked outcome till date about it. Therefore, the present manuscript discusses about the most frequently addressed image attacks e.g. image splicing and copy-move attack and elaborates the existing techniques presented by research community to resist it. The paper also contributes to explore the direction of present research trend with respect to tool adoption, database adoption, and technique adoption, and frequently used attack scenario. Finally, significant open research gap are explored after reviewing effectiveness of existing techniques.
COMPUTER VISION PERFORMANCE AND IMAGE QUALITY METRICS: A RECIPROCAL RELATION csandit
Computer vision algorithms are essential components of many systems in operation today. Predicting the robustness of such algorithms for different visual distortions is a task which can
be approached with known image quality measures. We evaluate the impact of several image distortions on object segmentation, tracking and detection, and analyze the predictability of this impact given by image statistics, error parameters and image quality metrics. We observe that
existing image quality metrics have shortcomings when predicting the visual quality of virtual or augmented reality scenarios. These shortcomings can be overcome by integrating computer vision approaches into image quality metrics. We thus show that image quality metrics can be
used to predict the success of computer vision approaches, and computer vision can be employed to enhance the prediction capability of image quality metrics – a reciprocal relation.
The new ORT HOPHOS XG 3D combines the advantages of 2D and 3D
into one comprehensive unit. With an extensive selection of panoramic
and cephalometric programs to choose from, the right 2D diagnostic
images are now augmented with the ability to capture 3D X-ray.
System to convert 2 d x-ray image into 3-d x-ray image in dentistryeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
An Experimental Study into Objective Quality Assessment of Watermarked ImagesCSCJournals
In this paper, we study the quality assessment of watermarked and attacked images using extensive experiments and related analysis. The process of watermarking usually leads to loss of visual quality and therefore it is crucial to estimate the extent of quality degradation and its perceived impact. To this end, we have analyzed the performance of 4 image quality assessment (IQA) metrics – Structural Similarity Index (SSIM), Singular Value Decomposition Metric (M-SVD) and Image Quality Score (IQS) and PSNR on watermarked and attacked images. The watermarked images are obtained by using three different schemes viz., (1) DCT based random number sequence watermarking, (2) DWT based random number sequence watermarking and (3) RBF Neural Network based watermarking. The signed images are attacked by using five different image processing operations. We observe that the metrics behave identically in case of all the three watermarking schemes. An important conclusion of our study is that PSNR is not a suitable metric for IQA as it does not correlate well with the human visual system’s (HVS) perception. It is also found that the M-SVD scatters significantly after embedding the watermark and after attacks as compared to SSIM and IQS. Therefore, it is a less effective quality assessment metric for watermarked and attacked images. In contrast to PSNR and M-SVD, SSIM and IQS exhibit more stable and consistent performance. Their comparison further reveals that except for the case of counterclockwise rotation, IQS relatively scatters less for all other four attacks used in this work. It is concluded that IQS is comparatively more suitable for quality assessment of signed and attacked images.
Automation systems, especially in the world of robotics, are becoming faster creating an increasing need to track objects at higher speeds than ever before.
Systems which rely on computer vision analysis to make artificial intelligence decisions and provide control, extend from high speed production lines and robot arms to autonomous guided vehicles, missiles and planes. Such systems use computer vision algorithms to extract information from images in a video sequence to identify and track objects in a scene. Usually these algorithms require high computational resources from a general purpose processor or a DSP, causing high computational latencies. High latencies act as a prohibitive factor for providing true, real time recognition and tracking of objects moving at high velocities.
Company Concurrent Vision ApS develops real time, high speed, vision-based systems that identify and track objects in a continuous video stream. These systems are based on the digital ASIC and FPGA technologies to implement high speed parallel computations providing true real time recognition and tracking of objects moving at speeds above 200 km/h. Typical applications of these systems include active video surveillance, vision- based robotic arms motion control, providing cognitive characteristics to robots and tracking high speed moving targets. Of other applications can be mentioned video stabilizing, augmented reality, image stitching, real time demosaicing for high definition video cameras, 3D imaging, intelligent toy and physical interactive computer games.
Concurrent Vision also provides solutions for the acceleration of high speed content based image retrieval systems that search for digital images in large databases. An example of such systems is retrieval and matching medical images for computer aided diagnosis.
Implementation of digital image watermarking techniques using dwt and dwt svd...eSAT Journals
Abstract
These days, in every field there is gigantic utilization of computerized substance. Data took care of on web and mixed media system framework is in advanced structure. Computerized watermarking is only the innovation in which there is inserting of different data in advanced substance, which we need to shield from illicit replicating. Computerized picture watermarking is concealing data in any structure (content, picture, sound and video) in unique picture without corrupting its perceptual quality. On the off chance that of Discrete Wavelet Transform (DWT), deterioration of the first picture is completed to insert the watermark. Moreover, if there should arise an occurrence of cross breed system (DWT-SVD) firstly picture is decayed by and after that watermark is installed in solitary qualities acquired by application of Singular Value Decomposition (SVD). DWT and SVD are utilized in combination to enhance the nature of watermarking. We have the procedures which are looked at on the premise of Peak Signal to Noise Ratio (PSNR) esteem at various benefits of scaling component; high estimation of PSNR is coveted because it displays great intangibility of the strategy.
Diabetic retinopathy also known as diabetic eye disease, is when damage occurs to the retina
due to diabetes. It can eventually lead to blindness. By analyzing and detecting vasculature structures
in retinal image the diabetes can be detected in advanced stages by comparing its states of retinal
blood vessels. In blood vessel classification approach computer based retinal image analysis can be
used to extract the retinal image vessels. Stationary wavelet transform (SWT) are used to extract the
features from the fundus image and classification can be performed using Support Vector
Machine(SVM). SVM has become an essential machine learning method for the detection and
classification of particular patterns in medical images. It is used in a wide range of applications for its
ability to detect patterns in experimental databases. If the vessels are present, then it is extracted by
using segmentation. Mathematical morphology and K-means clustering is used to segment the vessels.
To enhance the blood vessels and suppress the background information, smoothing operation can be
performed on the retinal image using mathematical morphology. Then the enhanced image is
segmented using K-means clustering algorithm to detect the diseases easily.
Reviewing the Effectivity Factor in Existing Techniques of Image Forensics IJECEIAES
Studies towards image forensics are about a decade old and various forms of research techniques have been presented till date towards image forgery detection. Majority of the existing techniques deals with identification of tampered regions using different forms of research methodologies. However, it is still an open-end question about the effectiveness of existing image forgery detection techniques as there is no reported benchmarked outcome till date about it. Therefore, the present manuscript discusses about the most frequently addressed image attacks e.g. image splicing and copy-move attack and elaborates the existing techniques presented by research community to resist it. The paper also contributes to explore the direction of present research trend with respect to tool adoption, database adoption, and technique adoption, and frequently used attack scenario. Finally, significant open research gap are explored after reviewing effectiveness of existing techniques.
COMPUTER VISION PERFORMANCE AND IMAGE QUALITY METRICS: A RECIPROCAL RELATION csandit
Computer vision algorithms are essential components of many systems in operation today. Predicting the robustness of such algorithms for different visual distortions is a task which can
be approached with known image quality measures. We evaluate the impact of several image distortions on object segmentation, tracking and detection, and analyze the predictability of this impact given by image statistics, error parameters and image quality metrics. We observe that
existing image quality metrics have shortcomings when predicting the visual quality of virtual or augmented reality scenarios. These shortcomings can be overcome by integrating computer vision approaches into image quality metrics. We thus show that image quality metrics can be
used to predict the success of computer vision approaches, and computer vision can be employed to enhance the prediction capability of image quality metrics – a reciprocal relation.
The new ORT HOPHOS XG 3D combines the advantages of 2D and 3D
into one comprehensive unit. With an extensive selection of panoramic
and cephalometric programs to choose from, the right 2D diagnostic
images are now augmented with the ability to capture 3D X-ray.
System to convert 2 d x-ray image into 3-d x-ray image in dentistryeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Advanced Fuzzy Logic Based Image Watermarking Technique for Medical ImagesIJARIIT
The segmentation algorithms vary for the types of medical images such as MRI, CT, US, etc.The current study work
can further be extended to develop a GUI tool based approach for separating the ROI. Additionally, a new technique of
separating ROI form the original image that will be applicable for all type of medical images can be evolved. Separated ROI
can be stored with xmin, xmax, ymin and ymax value so that at the end of embedding process before transmitting watermarked
image, the segmented ROI can be attached with watermarked image. Any medical image watermarking approach will be
suitable, if we segment the ROI from medical image with the four values, then embedding of watermark can be done on whole
medical image, in this paper work on different scan like ctscan ,brain scan etc. our results significant high than other.
Image Encryption Using Differential Evolution Approach in Frequency Domainsipij
This paper presents a new effective method for image encryption which employs magnitude and phase manipulation using Differential Evolution (DE) approach. The novelty of this work lies in deploying the concept of keyed discrete Fourier transform (DFT) followed by DE operations for encryption purpose. To this end, a secret key is shared between both encryption and decryption sides. Firstly two dimensional (2-D) keyed discrete Fourier transform is carried out on the original image to be encrypted. Secondly crossover is performed between two components of the encrypted image, which are selected based on Linear Feedback Shift Register (LFSR) index generator. Similarly, keyed mutation is performed on the real parts of a certain components selected based on LFSR index generator. The LFSR index generator initializes it seed with the shared secret key to ensure the security of the resulting indices. The process shuffles the positions of image pixels. A new image encryption scheme based on the DE approach is developed which is composed with a simple diffusion mechanism. The deciphering process is an invertible process using the same key. The resulting encrypted image is found to be fully distorted, resulting in increasing the robustness of the proposed work. The simulation results validate the proposed image encryption scheme.
Unified Approach With Neural Network for Authentication, Security and Compres...CSCJournals
The Present demands of scientific and social life forced image processing based applications to have a tremendous growth. This growth at the same time has given numbers of challenges to researcher to meet the desired objectives of either users or from solution perspectives. Among the various challenges, the most dominating areas are: reduction in required memory spaces for storage or taken transmission time from one location to other, protection of image contents to maintain the privacy and to facilitate the mechanism to identify the malicious modification if there is any either in storage or in transmission channel. Even though there are number of methods proposed by various researchers and are existed as solutions, questions are remain open in terms of quality, cost and complexity. In this paper we have proposed the concept based on neural network to achieve the quality of compression, protection and authentication all together using the ability of universal approximation by learning, one way property and one to one mapping characteristics correspondingly. With the proposed methods not only we can authenticate the image but also positions of malicious activity given in the image can be located with high precision. Proposed methods are very efficient in performance as well as carry the features of simplicity and cost effectiveness.
Reversible Data Hiding Using Contrast Enhancement ApproachCSCJournals
Reverse Data Hiding is a technique used to hide the object's data details. This technique is used to ensure the security and to protect the integrity of the object from any modification by preventing intended and unintended changes. Digital watermarking is a key ingredient to multimedia protection. However, most existing techniques distort the original content as a side effect of image protection. As a way to overcome such distortion, reversible data embedding has recently been introduced and is growing rapidly. In reversible data embedding, the original content can be completely restored after the removal of the watermark. Therefore, it is very practical to protect legal, medical, or other important imagery. In this paper a novel removable (lossless) data hiding technique is proposed. This technique is based on the histogram modification to produce extra space for embedding, and the redundancy in digital images is exploited to achieve a very high embedding capacity. This method has been applied to various standard images. The experimental results have demonstrated a promising outcome and the proposed technique achieved satisfactory and stable performance both on embedding capacity and visual quality. The proposed method capacity is up to 129K bits with PSNR between 42-45dB. The performance is hence better than most exiting reversible data hiding algorithms.
Image Authentication Using Digital Watermarkingijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
There is great research in the field of data security these days. Storing information digitally in the cloud and transferring it over the internet proposes risks of disclosure and unauthorized access, thus users, organizations and businesses are adapting new technology and methods to protect their data from breaches. In this paper, we introduce a method to provide higher security for data transferred over the internet, or information based in the cloud. The introduced method for the most part depends on the Advanced Encryption Standard (AES) algorithm. Which is currently the standard for secret key encryption. A standardized version of the algorithm was used by The Federal Information Processing Standard 197 called Rijndael for the Advanced Encryption Standard. The AES algorithm processes data through a combination of Exclusive-OR operations (XOR), octet substitution with an S-box, row and column rotations, and a MixColumn operations. The fact that the algorithm could be easily implemented and run on a regular computer in a reasonable amount of time made it highly favorable and successful.
In this paper, the proposed method provides a new dimension of security to the AES algorithm by securing the key itself such that even when the key is disclosed, the text cannot be deciphered. This is done by enciphering the key using Output Feedback Block Mode Operation. This introduces a new level of security to the key in a way in which deciphering the data requires prior knowledge of the key and the algorithm used to encipher the key for the purpose of deciphering the transferred text.
Keywords: Keywords: Keywords: Keywords: Keywords: Keywords: Keywords:
Abstract
There is great research going on in the field of data security nowadays. Protecting information from disclosure and breach is of high importance to users personally and to organizations and businesses around the world, as most of information currently are sensitive electronic information transferred over the internet and stored in cloud based system. In this paper, we propose a method to increase the security of messages transferred on the internet, or information stored in the cloud. Our proposed method mainly relies on the Triple Data Encryption Standard (TDES) algorithm. TDES is intact the Data Encryption Standard repeated three times in succession to encrypt data. TDES is considered highly secure as there is no applicable method to break the code itself without knowing the key. We propose to encrypt the key using Cipher Feedback Block algorithm, before using TDES to encrypt data. Such that even when the key is disclosed, the key itself cannot decipher the ciphered text without enciphering the key with CFB. This introduces a new dimension of security to the TDES algorithm.
The method introduced in this paper increases the security of the TDES algorithm using CFB algorithm by increasing the key security, such that it is actually not possible to decipher the text without prior knowledge and agreement of key and algorithms used.
Keywords: Data Encryption Standard, Triple Data Encryption Algorithm, Cipher Feedback Block.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Leading Change strategies and insights for effective change management pdf 1.pdf
Renas Rajab Asaad
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Image Forgery Detection Using the Pixel-wise Fragile Image
Watermarking Method in Spatial Domains
Yasir Ahmed Hamza Renas Rajab Asaad
Assistant Lecturer Assistant Lecturer
Faculty of Computer & Information Technology - Nawroz University
كورتى
ث جةندين و فوتوشوب ادوبي َيثروطرام وةك بوينة بةالف بةر زور َيَوةكيبش َنايو لسةر َكرنيكارث و طهورين َنيثروطرام ,دوماهيكان لفانلسةر َيَكرنيكارت َتيجور هندةك هةروةسا .دي َنيروطرام
بةرزةكرن َتةيده َنةييو يئ َينثاراست َيفما دياركرنا َيذبةرهند .كرن هاتية َيل طهورين َيجه دياربكةن َنينةش جاف كرن َنةيده َنةييوهةر دياركرنا بو هاريكارة َيثروطرامةك َتفييث جورة ئةف و
.َنةيدايدو َيطهورينةكل كاركرن بو دياركرن هاتية نوي َكةكاير ,الثةرةيدا َيلف( َكايبر َنةييو َتيَكسليث سةرwatermarking( دطةل يئ َينينه َيَمايةكيه َكةير ئةف .)watermarkingخو طةل )
( دطةل هةلكريتcheck-bits( ثانيا و َذييدر ب رةطاورةنط َينَيلو كةسكدا َيرةنط ل )215x215( َسايبروس دطةل هةلطرتن َمايه .)watermarkingت وةك كةسك َيرةنط لسةر )َيشرتةجن َيةختةي
( ثانيا و َذييدر ب215*215( َكاير هةروةسا .كةفةري ذ َنةييو ذ ثارجةك ل بةردةوام َتيبت ئاريشا نةبونا ذبو )WEITPلسةر َيطهورينةك هةر نةبونا يان هةبون كرنا تةكيد بو بكارئينان َتةيده )
( َكاير َيهند ذبةر .َنةييوwatermarking and tamperingَتةيده )لفي دياركرن هاتينة َتيئةجنام لديف .هنارتن هاتية َيَنةييو ل كرن هاتية َيل طهورين َيجه دياركرنا بو بكارئينان
( دطةل دبيت َميك َنةييو َتيَكسليب بونا ووندا و دبيت زئدة َنةييو يا َيتيكوال كو دياردبيت الثةرةيداwatermarkingَينرخ بكارئينانا لديف )PSNRشي هةروةسا .َيطهورينةك هةر ديتنا انا
َدةكرنايز ب َنةيدايدوobjects( َيجور ذ َنةييو وبكارئيناناJPEG compression( َريلذ )watermarkingيف َربنايذ .)objectذ(watermarkingثاشان وي دووبارةبونا دطةل )
.َنةييو لسةر َيتيكستةك نفيسينا
املستخلص
ميالرقمية تغيريالصور كنحاليا( مثل الصور لتحرير متطورة برامج استخدام عرب بسهولةAdobe Photoshop®ميكن .)الصور بعض اىل النظرالصور غرار على فيها املتالعب الصور بعض
بأنه اشتباه أي دون األصليةجرى.ُاايض تعديلهموعليهصعبة مهمة عليها املصادقة جيعل الصورة لتحرير الربامج هذه مثل استخدام فانل الصورة هذه استخدام يصبح ورمباالااحماكم ي بثبا
مستحيال. يالبحثية الورقة هذهمت ،طريقة على باالعتماد اهلشة املائية للعالما جديدة طريقة اقرتاحPixel-wiseوبتا السرية املائية العالمة تضمني على املقرتحة الطريقة هذه وتستند .
ا لصورة اخلضراء طبقة ي التحققحجم ذا امللونة لغطاء512x512احلجم ذا الشطرنج لوحة كانها اخلضراء الطبقة املائية العالمة تضمني عملية تعامل .x512206التتابعي التضمني لتجنب
استخدام يتم .الغطاء لصورة املكانية اجملاال ي للبتااملائية بالعالمة التالعب ومتييز استخراج عمليةإذ فيما للتاكد،لذلك .ال أم اخلصم قبل من املائية للعالمة املتضمنة الصورة ي التالعب كان ا
ل التالعب مصفوفة و املستخرجة املائية العالمة استخدام يتمل.املرسلة املائية للعالمة املتضمنة الصورة من تحققووتشويه عالية جودة املقرتحة الطريقة تقدم ،التجريبية النتائج على اعتمادا
منخقيم على اعتمادا املائية للعالمة املتضمنة الصور ي فضPSNR.هلماملتضمنة الصورة إىل كائنا إضافة مثل حاال ي املائية للعالمة املتضمنة الصورة ي بالتالعب التعرف على القدرة ،كذلك
ضغط وتطبيق ، املائية للعالمةJPEGوإزالة ، املائية للعالمة املتضمنة الصورة علىواضافة ، املائية للعالمة املتضمنة الصورة على الكائن تكرار ،املائية للعالمة املتضمنة الصورة من الكائنا
املائية للعالمة املتضمنة الصورة على النصوص.
Abstract
Digital images can be changed easily nowadays through the use of sophisticated software to edit images such as (Adobe
Photoshop®). You can look at some manipulated pictures along the lines of the original images without any suspicion that they
are also modified. Accordingly, the use of such software to edit the image makes ratification a difficult task and the use of this
image in the courts for proving may become impossible.In this paper, a new method has been proposed for water fragile signs
depending on the method of Pixel-wise. The proposed method is based on the included secret watermark and check bits in the
green layer to the image of the colorful cover with the size of 512x512. The process of including watermark deals with the green
class as a chess board with 512 x 512 sizes to avoid the inclusion of sequential bits in the spatial areas of the image of the
cover. The process of extracting and discriminating the manipulation of watermark is used to determine whether the
manipulation of the image containing watermark was done by an opponent or not. Therefore, the use of the extracted
watermark and matrix manipulation to check the image containing watermark sent. Depending on the experimental results, the
proposed method provides high quality, low distortion in the images contained watermark PSNR depending on their values.
Also, the ability to recognize manipulation in the picture containing watermark in cases such as adding objects to the image
containing the watermark, and the application of JPEG compression on image containing watermark, and removing objects
from the image containing watermark, repeating the object image containing watermark, and adding a text on image including
watermark
Keywords: Check-bits, Fragile watermarking, PSNR, Secret watermark, Watermarked-image.
1. Introduction
The digitization of multimedia contents makes them more reliable, with quick and efficient storage,
processing and sending [1]. These features of the multimedia contents may lead to concerns such as
performing illegal copies and redistributing them. The Multimedia contents such as image, sound, text,
and video, can be easily altered and reproduced in a digital domain using nowadays multimedia
editing software [1], [2]. An image can be equivalent to a thousand of words, but it may have tens of
interpretations [2]. For the time being, the images can be altered easily by various sophisticated
image editing softwares such as (Adobe Photoshop®). Also, some of the manipulated images can be
seen similar to the original images without any suspicion that they have been modified. As such, using
such software for image editing makes the authentication of it a challenging mission and the use of
the image for evidencing in the courts of law becomes impossible. Digital image forensics is an area
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that analyzes images in such scenarios to verify credibility and authenticity through various
techniques. This makes it a popular domain because of its potential applications in many fields, such
as legal documents, news reporting, medical imaging and insurance claim investigations [2]. Digital
images require techniques for dealing with the problems associated with them. Therefore, it is
important to develop methods for protecting the images such as copyright protection, protection
against duplication and owner's authentication [1], [3]. One of these methods is image watermarking.
This technique is a special field of data hiding that can be applied to protect images against those
types of manipulations and duplications. Digital image watermarking is a technique to verify the owner
identification of the image and inhibit the unauthorized copying. This process is done by embedding
the secret data called (Watermark) in the image. The watermark could be a logo of the owner’s or
controlled information embedded in the image contents [1], [3]. The process that embeds the
watermark in the image is called (Embedding Process). The image that is used for embedding the
watermark in it is called (Cover-image). After the embedding process is done, the cover-image is
converted into watermarked-image. Another process used to extract/detect the watermark from the
image called (Extraction/Detection Process). During this process, the extraction/detection process
applied on watermarked-image to extract/detect the watermark. There are some criteria that used to
classify the digital image watermarking techniques such as (robustness, perceptibility and embedding
and extraction/detection methods) [1]. Also, image watermarking techniques can be divided into two
main types. The first type is based on robustness that makes the embedded watermark resist
common image processing operations such as filtering, image compression,….etc. Accordingly, this
type is used for ownership verification [1], [4], [5]. The second type is based on the fragileness called
(Fragile Watermarking) and is used to check authenticity and integrity of digital images [4]-[9]. The
fragile image watermarking techniques are developed with an objective to identify and find any
possible tampered in the watermarked image [3], [4], [7]. In fragile image watermarking, if any
modification is done on the watermarked-image, the watermark removes from it. This means that the
watermarked-image has been tampered. Digital Image verification of its integrity and authentication
are usually fragile in sensing. This means that when watermarked-image is attacked, the embedded
watermark should be entirely or locally removed, according to the type of the attack on the whole or
partial tampering. Therefore, the watermark extraction/detection raises alarms for wrong watermark
[1]. The pure cryptography methods for authentication are usually compared with fragile image
watermarking methods. But, the difference between pure cryptography and fragile image
watermarking is the latter’s capability to find the tampered or damaged areas depending on the
distortion in watermarked-image. Fragile image watermarking methods have some properties [1], [10]:
Detection of tampering in the watermarked-image.
The embedded watermark must have perceptual transparency.
Blind detection without requiring the original image.
The Detector should be able to find and characterize manipulations made to a watermarked- image.
The watermarking secret-key spaces should be large.
The embedding of a watermark by unauthorized parties should be hard.
The fragile image watermarking can be classified into two types: Block-wise fragile watermarking and
Pixel-wise fragile watermarking [4], [7], [8]. In block-wise fragile watermarking, the cover-image is
divided into blocks and watermark information is derived from the necessary content of the block of
the cover-image. In case the watermarked-image is modified, the tampered block and watermark
contained in that block will mismatch. By this inequality, the tampered block can be identified easily
[4], [7], [8]. Block-wise methods identify the tampered block of watermarked-image, but not the
tampered pixels. In Pixel-wise fragile watermarking, the watermark information derived from gray
values of cover-image pixels is embedded into the cover-image pixels themselves. Therefore, the
tampered pixel values of watermarked-image can be identified due to the loss of watermark
information that they carry. In this paper, a new method of pixel-wise based fragile image
watermarking has been proposed. The proposed method is based on embedding the secret
watermark and Check-bits in Green layer of colored cover-image of size 512x512. The watermark
embedding process treats the Green layer as Chess-board of size 512x512 to avoid the sequentially
embedding bits in spatial domains of cover-image. The watermark extraction and identification
tampering process is used for ensuring whether the watermarked image has been tampered by the
adversary or not. As such, extracted watermark and tampering matrix are used for authenticating the
watermarked-image sender’s purposes. Depending on the experimental results, the proposed method
presents a high quality and a low distortion in the watermarked-image according to PSNR values. The
method also helps in identifying the tampering on the watermarked-image in situations such as adding
objects to watermarked-image, applying the JPEG compression on watermarked-image, removing
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objects from watermarked-image, duplicating the object on the watermarked-image, and adding texts
on the watermarked-image.
2. Literature Review
There are several methods of fragile image watermarking that have been proposed. In [4], the
researchers proposed a method of fragile image watermarking which enabled them to find the
tampered locations in watermarked-image and recover these locations without any error. The
proposed method is the block-wise type. During the embedding process, the cover-image is divided
into 8x8 non-overlapping blocks. For each block, it computes the reference-bits that depend on the
cover-image and check-bits determined by the cover-image content and reference-bits. These two
types of bits as watermarks are embedded into all blocks of the cover-image using a difference
expansion embedding algorithm. The result of the embedding process is a watermarked-image which
then would be sent across the communication channel. On sending the watermarked-image, some of
its content may be modified with some fake information. Accordingly, the watermarks embedded in it
may be removed in the tampered locations of the watermarked-image. Yet the other blocks of the
watermarked-image with their untampered watermarks remain unaffected. During the
extraction/detection process, the check-bits, extracted from each block of watermarked-image and
compared with computed check-bits, are used to identify the tampered blocks. Then, the reference-
bits are extracted from the remaining blocks to recover the original content of the image. Therefore,
the original image can be recovered and restored without any error. Due to tampering, the content
replacement may destroy a part of the embedded watermark as long as the altered area is not too
extensive. A further method of fragile watermarking is proposed in [5]. This method is designed for
recovering the weaknesses of the chaotic watermarking scheme for the authentication of Joint
Photographic Experts Group JPEG images method. So, the proposed method presents a new version
that is capable of resisting attacks, less perceptible and with faster processing. During the embedding
process, the proposed algorithm applied the Discrete Cosine Transform DCT on the cover-image to
embed the watermark in the coefficients of LSB. Also, it used robust chaotic generators to generate
dynamic keys and watermarking information. According to the results of the proposed technique, it is
capable of verifying integrity of the image contents that are sent across the Internet. In [6], the
researchers proposed a block-wise semi-fragile image watermarking method. The proposed
technique uses the logistic map to encipher the features extracted from the original image and then
generate a watermark to embed it in the middle frequency of DCT coefficients of each block of cover-
image. During the extraction/detection process, the features extracted from each block of the
watermarked-image were deciphered. They were then compared with the reconstructed feature
information to generate the tamper array. The tampered block of watermarked-image can be
recovered by using bicubic interpolation. The results of this method are represented by good
imperceptibility for watermarked-image, sensitivity for malicious tampering and capability to identify
and approximately recover tampered areas in watermarked-image. In [7], a pixel-wise fragile image
watermarking was proposed for authentication and tamper localization. During the embedding
process, the secret key was used to scramble the watermark and the integer wavelet transform
applied on cover-image to obtain the four sub-bands (Low-low LL, High-low HL, Low-high and High-
high HH). Then, the watermark was embedded in HH sub-bands coefficients by using odd-even
mapping method. According to the results, the proposed method is good in the detection and
localization of tampered pixels of the watermarked-image. A method of block-wise fragile image
watermarking that depends on k-medoids clustering approach is proposed in [8]. At the embedding
process, the cover-image was divided into 4x4 non-overlapping blocks and for each block, (48) bits
that represent (45) bits of recovery bits and (3) bits for authentication process called (Union bit,
Affiliation bit and Spectrum bit respectively) were calculated. For each block, the authentication bits
are computed by extracting (5) most significant bits MSB of pixel values of the block and the hash
functions applied on them. Also, the recovery (45) bits are calculated by applying the means of
derived clusters and its corresponding mapping bits. Then, by using the secret key, the (48) bits of
each block are mapped pseudo-randomly. At the extraction process, the authentication bits extracted
from watermarked-image and compared with further computed authentication bits were used to
identify the tampering in block. In the case of image recovery, the extracted recovery bits of each
block are used to recover the contents of cover-image. The results of this method show a capability of
identifying and restoring the tampered block effectively with good imperceptibility. A fragile image
watermarking that depends on block-wise for medical image is proposed in [9]. In this method, the
cover-image is divided into three regions called Region of Interest ROI, Region of Non Interest RONI
and border pixels. Then, the Electronic Patient Record and authentication data of ROI computed by
using the hash function message digest MD5 of the medical image are compressed using the Run
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Length Encoding and embedded in border pixels. Also, the calculated recovery information is
embedded in the RONI. At the extraction process, the integrity of ROI is verified in order to identify the
tampered blocks inside ROI. So, the original blocks of ROI can be recovered from the RONI by simple
mathematical calculations. According to its results, the proposed method was capable to generate
high-quality watermarked medical image and identify and recover the tampered blocks in the ROI.
3. Proposed Method
The proposed method is divided into three processes, namely watermark generation process,
watermark embedding process and watermark extraction and identification tampering process
WEITP.
3.1.Watermark Generation Process
This process represents the initial step of the proposed method. According to this method, a colored
cover-image of size 512x512 was converted into a grayscale image and then converted into a binary
(Black/White) image. After that, the binary image was resized into half, i.e. the size of the binary
image has become 256x265 which represents the watermark. In order to increase the security of the
watermark, the Blum-Blum-Shub BBS pseudorandom bit generator PRBG is used to create the
pseudorandom bits array PBA. The BBS PRBG is then summarized in the following steps:
Choose two prime numbers according to the condition:
(1)
Compute the value of
Choose another positive integer number as and its value must be in range [ , and
. (2)
Repeat the following step along the size of PBA that equals the size watermark 256x256:
(3)
Where
The output XOR-ed with the watermark to generate the final secret watermark.
Fig.1. shows the secret watermark generation process of Lena cover-image.
Fig.1: The secret watermark generation process for Lena cover-image.
3.2.Watermark Embedding Process
This process is used to embed the secret watermark in the cover-image after the first process of
watermark generation. The embedding process works as follows:
The colored cover-image splits into three layers (Red, Green, and Blue).
Choose the Green layer for embedding the secret watermark bits and Check-bits.
The embedding process handles the Green layer as Chess-board of a size equivalent to Green
layer’s size and this means that all white indices are used for embedding all bits of secret
watermark. Each secret watermark bit is embeded in each third LSB of pixel values. While black
indices are used for embedding three Check-bits in each pixel values after converting the pixel
values from decimal into the binary representation and setting the values of the first, second and
third LSBs are set respectively into one. Fig.2. illustrates the Check-bits embedding method.
Watermark
PBA
XOR
Secret
Watermark
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Fig.2: The Check-bits embedding method.
The Green layer merges with other (Red and Blue) layers to generate the final watermarked image.
Fig.3. shows the watermark embedding process.
3.3.Watermark Extraction and Identification Tampering Process
The watermarked-image sends to the receiver across the communication channel such as the
Internet. During the transferring of the watermarked-image, the adversary may alter it by adding or
removing some objects using image editing software such as (Adobe Photoshop®) supposing that the
adversary is professional in using these kinds of the software. Therefore, the alteration in
watermarked-image cannot be detected by naked-eyes. In this case, the WEITP is required to check
and identify whether the watermarked-image is tampered or not, and determine the tampered any.
WEITP works as follows:
The watermarked-image is split into three layers (Red, Green, and Blue).
Choose the Green layer for extracting the secret watermark bits and Check-bits.
Initialize a new Tampering Matrix TM with zero values which are equal to the size of the Green layer.
The WEITP handles the Green layer as Chess-board, i.e. all white indices are used for extracting all
bits of the secret watermark from the third LSB of each pixel value and put the values sequentially in
another array called extracted secret watermark array ESWA. Black indices are used for extracting
the three Check-bits from each pixel value after converting it from decimal into the binary
representation and taking the first, second and third LSBs respectively. If the (LSB1
st
, LSB2
nd
and
LSB3
rd
) of check-bits of each pixel value do not equal one, this would mean that this pixel has been
tampered. It has also set the tampering matrix value in those pixel value indices to be (255), otherwise
it would be set to (0) according to the equation. Fig.4. illustrates the Check-bits extracting method.
{ (4)
Where,
Fig.4: The check-bits extracting method.
100
Convert into
Binary
0 1 1 0 0 1 0 0
Embed
Check-bits
0 1 1 0 0 1 1 1
Most Significant Bits
MSB
LSB
Pixel Value
103
Pixel Value
After embedding
LSB2LSB3 LSB1
103
Convert into
Binary
0 1 1 0 0 1 1 1
Extract
Check-bits
0 1 1 0 0 1 0 1
Most Significant Bits
MSB
LSB
Pixel Value
255TM (i,j)
LSB3 LSB2 LSB1
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Fig.3: The watermark embedding process.
Apply BBS
PRBG
Read p, q and seed Read Cover-image
Split into Three
Layers (Red,
Green and Blue)
Convert into
Grayscale
Image
Convert into
Binary Image
And resized it
Output
PBA
Apply
XOR
Secret
Watermark
Embed Check-bits in each
Black index of Green layer
Embed all Bits
In White indices
of Green layer
Output
Green layer
Output Watermarked-image
Merge the
Layers (Red,
Green and Blue)
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Apply BBS PRBG to generate the PBA and XOR-ed with ESWA in order to obtain the watermark.
Show the watermark and tampering matrix. Fig.5. shows the watermark extraction and
identification tampering process.
Fig.5: The watermark extraction and identification tampering process.
4. Experimental Results
The proposed method has been implemented using the language of technical computing Matlab®
R2009a. So, two programs have been written. The first program is used for embedding the watermark
and Check-bits in the Green layer of the cover-image including the watermark generation process and
generating the watermarked-image. The second program is used for extracting the watermark, finding
the tampering in the watermarked-image and displaying the result in tampering matrix as an image.
Six colored cover-images of the same size 512x512 have been chosen frequently for testing the
performance of data hiding methods. Fig. 6 shows these cover-images after embedding the secret
watermarks and Check-bits as a result of watermarked-images. Also, the reason for selecting the
Green layer for embedding the secret watermark and Check-bits is that the values of peak signal to
noise ratio PSNR of the Green layer, are greater than (Red and Blue) layers PSNR values. PSNR is
the measurement used to compute the quality of the watermarked-image in a metric unit called
decibels. If the value of PSNR is high, this would mean that the quality of watermarked-image is high
and there will be little distortion. Otherwise, if the value of PSNR is low, this would mean a high
distortion in the watermarked-image. In order to compute the PSNR, the mean square error MSE
must be firstly calculated according to the following equation:
MSE= ∑ ∑ (5)
Where, CI is cover-image of size (M x N) and WI is watermarked-image (M x N), 1≤ i ≤ M, 1≤ j ≤ N.
Then the following equation is used to calculate PSNR:
PSNR=10* (6)
If the cover-image is a grayscale image of integer values [0-255], then R=255. Fig.7. illustrates the
PSNR for each (Red, Green, and Blue) layer of watermarked-images.
Apply BBS
PRBG
Read p, q and seed Read Watermarked-image
Split into Three
Layers (Red,
Green and Blue)
Output
PBA
Apply
XOR Extract all Bits
of Secret Watermark
from White indices
Output
Green layer
Tampering
Matrix
Extract all Check-bits
from all Black indices
Watermark
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46.2
46.4
46.6
46.8
47
47.2
47.4
47.6
47.8
48
48.2
48.4
48.6
48.8
49
49.2
Lena Baboon Parrot Peppers Barbara F-16
Red Layer PSNR
Green Layer PSNR
Blue Layer PSNR
Fig.6: A set of watermarked-images (a) Lena,
(b) Baboon, (c) Parrot, (d) Peppers, (e) Barbara, (f) F-16
Fig.7: PSNR for each (Red, Green, and Blue) layer of watermarked-images.
To test the performance of the proposed method against the tampering in the watermarked-image, a
flower has been added to Lena watermarked-image and WEITP has been applied on it. The result of
tampering matrix and extracted watermarked are shown in Fig. 8. Also, the parrot and the text
“Barbara” have been added to Barbara watermarked-image and WEITP has been applied on it. The
results of tampering matrix and extracted watermarked are shown in Fig. 9. According to these
results, the proposed method is capable of identifying the tampering in watermarked-image and the
effect of tampering on the extracted watermark.
(a) (b) (c)
(d) (e) (f)
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Fig. 8: The tampering in Lena watermarked-image (a) Original watermarked-Lena image,
(b) Tampered watermarked-Lena image, (c) Tampering matrix, (c) Extracted watermark
Fig. 9: The tampering in Barbara watermarked-image (a) Original watermarked-Barbara image,
(b) Tampered watermarked-Barbara image, (c) Tampering matrix, (c) Extracted watermark
JPEG compression is a kind of lossy compression that is widely used in image operations [6]. To test
the proposed method against JPEG compression, the Barbara watermarked-image has been
compressed by JPEG compression and WEITP has been applied on the compressed Barbara
watermarked-image. The results are shown in Fig.10. According to these results, the proposed
method presents fragility against this type of compression and the extracted watermark is completely
damaged. The damaging of watermark can serve the adversary in eliminating the authentication for
watermarked-image. In this case, the authentication of watermarked-image will depend on the
tampering matrix that explains the effect of theadversary operation on the watermarked-image.
Fig. 10: The JPEG compression on Barbara watermarked-image (a) Original watermarked-Barbara image,
(b) Compressed watermarked-Barbara image, (c) Tampering matrix, (c) Extracted watermark
Another kind of tampering has been applied on the watermarked-image by adding the F-16 object
from the original F-16 image to the F-16 watermarked-image and WEITP has been applied on the
(a) (b) (c) (d)
(a) (b) (c) (d)
(c) (d)(a) (b)
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(a) (d)(c)(b)
tampered F-16 watermarked-image. The results of tampering matrix and extracted watermarked are
shown in the Fig. 11. In the light of these results, the proposed method is capable of identifying
tampering in such situations.
Fig. 11: The tampering on F-16 watermarked-image (a) Original watermarked- F-16 image,
(b) Tampered watermarked-F-16 image, (c) Tampering matrix, (c) Extracted watermark
In addition to that, another kind of tampering has been applied on the watermarked-image by
transforming watermarked- Baboon image into half. Also, another half part of Peppers image has
been added to it, then WEITP has been applied on the tampered Baboon watermarked-image. The
results of tampering matrix and extracted watermarked are shown in the Fig. 12. According to these
results, the proposed method is capable of identifying tampering in such situations.
Fig. 12: The tampering on Baboon watermarked-image (a) Original watermarked- Baboon image,
(b) Tampered watermarked-Baboon image, (c) Tampering matrix, (c) Extracted watermark
Suppose that the adversary has tampered the watermarked- image by adding texts on it. In this case,
WEITP will be applied on the tampered watermarked- Parrot image to identify the tampering. The
results of this process are shown in the Fig. 13. In the light of these results, the proposed method is
capable of identifying the effect of tampering on the tampering matrix and extracted watermark.
Fig. 13: The tampering on Parrot watermarked-image (a) Original watermarked- Parrot image,
(b) Tampered watermarked-Parrot image, (c) Tampering matrix, (c) Extracted watermark
(a) (b) (c) (d)
(a) (b) (c) (d)
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To compare the proposed method with other methods that have been proposed for fragile image
watermarking according to PSNR values, Table (1) shows PSNR value for each method using Lena
image as a watermarked-image. According to PSNR values, the proposed method presents better
preserving quality for watermarked-image among other methods. In the method that proposed in [7],
the value of PSNR is higher than the value of PSNR for the proposed method. Because this method
used a grayscale Lena image as a watermarked-image. While the proposed method used a color
Lena image as a watermarked-image. In addition, this method applies the embedding process on
watermarked-image using a wavelet transform domain, while the proposed method applies the
embedding process on watermarked-image using a spatial domain.
Table (1) PSNR for each method
Watermarking Scheme PSNR in Decibels (dB)
Method in [8] 40.2 dB
Method in [7] 60.9 dB
Method in [6] 44.2 dB
Method in [4] 29.6 dB
The Proposed Method 48.0 dB
5. Conclusion
In this paper, a new method of pixel-wise based fragile image watermarking has been proposed. The
proposed method is based on embedding the secret watermark and Check-bits in a Green layer of
colored cover-image of size 512x512. The watermark embedding process treats the Green layer as
Chess-board of size 512x512 to avoid the sequentially embedding bits in the spatial domains of
cover-image. According to this method, the white indices are used to embed all the bits of the secret
watermark in the Green layer pixel values, while the black indices are used to embed all the Check-
bits in the Green layer pixel values. The reason behind choosing the Green layer of cover-image for
the embedding process is that the values of PSNR for Green layer are the highest among (Red and
Blue) layers. The WEITP is used for ensuring whether watermarked image has been tampered by
adversary or not. Therefore, extracted watermark and tampering matrix are used for authenticating
the watermarked-image sender’s purposes. Depending on the experimental results, the proposed
method presents a high quality and low distortion in the watermarked-image according to PSNR
values. The method also helps in identifying the tampering on the watermarked-image in situations
such as adding objects to watermarked-image, applying the JPEG compression on watermarked-
image, removing objects from watermarked-image, duplicating the object on the watermarked-image,
and adding texts on the watermarked-image. The proposed method can be used for authenticating
purposes of digital colored images and preventing their forgery. But, the restoration of watermarked-
image to its original watermarked-image after tampering is required in some situations. Therefore,
such a requirement can be addressed for future work.
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