JP INFOTECH is one of the leading Matlab projects provider in Chennai having experience faculties. We have list of image processing projects as our own and also we can make projects based on your own base paper concept also.
For more details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/matlab-projects/
HUMAN VISION THRESHOLDING WITH ENHANCEMENT FOR DARK BLURRED IMAGES FOR LOCAL ...cscpconf
There are several images that do not have uniform brightness which pose a challenging problem
for image enhancement systems. As histogram equalization has been successfully used to correct
for uniform brightness problems, a histogram equalization method that utilizes human visual
system based thresholding(human vision thresholding) as well as logarithmic processing
techniques were introduced later . But these methods are not good for preserving the local
content of the image which is a major factor for various images like medical images.Therefore
new method is proposed here. This method is referred as “Human vision thresholding with
enhancement technique for dark blurred images for local content preservation”. It uses human
vision thresholding together with an existing enhancement method for dark blurred images.
Experimental results shows that the proposed method outperforms the former existing methods in
preserving the local content for standard images and medical images
Super-Spatial Structure Prediction Compression of Medicalijeei-iaes
The demand to preserve raw image data for further processing has been increased with the hasty growth of digital technology. In medical industry the images are generally in the form of sequences which are much correlated. These images are very important and hence lossless compression Technique is required to reduce the number of bits to store these image sequences and take less time to transmit over the network The proposed compression method combines Super-Spatial Structure Prediction with inter-frame coding that includes Motion Estimation and Motion Compensation to achieve higher compression ratio. Motion Estimation and Motion Compensation is made with the fast block-matching process Inverse Diamond Search method. To enhance the compression ratio we propose a new scheme Bose, Chaudhuri and Hocquenghem (BCH). Results are compared in terms of compression ratio and Bits per pixel to the prior arts. Experimental results of our proposed algorithm for medical image sequences achieve 30% more reduction than the other state-of-the-art lossless image compression methods.
AN OPTIMIZED BLOCK ESTIMATION BASED IMAGE COMPRESSION AND DECOMPRESSION ALGOR...IAEME Publication
In this paper, we implemented a new model of image compression and decompression method to search the aimed image based on the robust image block variance estimation. Many methods of image compression have been proposed in the literature to minimize the error rate and compression ratio. For encoding the medium type of images, traditional models use hierarchical scheme that enables the use of upper, left, and lower pixels for the pixel prediction, whereas the conventional raster scan prediction methods use upper and left pixels. In this proposed work, we have implemented block estimation and image distortion rate to optimize the compression ration and to minimize the error rate. Experimental results show that proposed model gives a high compression rate and less rate compared to traditional models.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
HUMAN VISION THRESHOLDING WITH ENHANCEMENT FOR DARK BLURRED IMAGES FOR LOCAL ...cscpconf
There are several images that do not have uniform brightness which pose a challenging problem
for image enhancement systems. As histogram equalization has been successfully used to correct
for uniform brightness problems, a histogram equalization method that utilizes human visual
system based thresholding(human vision thresholding) as well as logarithmic processing
techniques were introduced later . But these methods are not good for preserving the local
content of the image which is a major factor for various images like medical images.Therefore
new method is proposed here. This method is referred as “Human vision thresholding with
enhancement technique for dark blurred images for local content preservation”. It uses human
vision thresholding together with an existing enhancement method for dark blurred images.
Experimental results shows that the proposed method outperforms the former existing methods in
preserving the local content for standard images and medical images
Super-Spatial Structure Prediction Compression of Medicalijeei-iaes
The demand to preserve raw image data for further processing has been increased with the hasty growth of digital technology. In medical industry the images are generally in the form of sequences which are much correlated. These images are very important and hence lossless compression Technique is required to reduce the number of bits to store these image sequences and take less time to transmit over the network The proposed compression method combines Super-Spatial Structure Prediction with inter-frame coding that includes Motion Estimation and Motion Compensation to achieve higher compression ratio. Motion Estimation and Motion Compensation is made with the fast block-matching process Inverse Diamond Search method. To enhance the compression ratio we propose a new scheme Bose, Chaudhuri and Hocquenghem (BCH). Results are compared in terms of compression ratio and Bits per pixel to the prior arts. Experimental results of our proposed algorithm for medical image sequences achieve 30% more reduction than the other state-of-the-art lossless image compression methods.
AN OPTIMIZED BLOCK ESTIMATION BASED IMAGE COMPRESSION AND DECOMPRESSION ALGOR...IAEME Publication
In this paper, we implemented a new model of image compression and decompression method to search the aimed image based on the robust image block variance estimation. Many methods of image compression have been proposed in the literature to minimize the error rate and compression ratio. For encoding the medium type of images, traditional models use hierarchical scheme that enables the use of upper, left, and lower pixels for the pixel prediction, whereas the conventional raster scan prediction methods use upper and left pixels. In this proposed work, we have implemented block estimation and image distortion rate to optimize the compression ration and to minimize the error rate. Experimental results show that proposed model gives a high compression rate and less rate compared to traditional models.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A REGULARIZED ROBUST SUPER-RESOLUTION APPROACH FORALIASED IMAGES AND LOW RESO...cscpconf
This paper presents a hybrid approach for images and video super-resolution. We have proposed the approach for enhancing the resolution of images and low resolution, under
sampled videos. We exploited the shift and motion based robust super-resolution (SR)algorithm [1] and the diffusion image regularization method proposed in [2] to obtain the alias free and jerk free smooth SR image.We presented a framework for obtaining super-resolution video thatis robust,even in the presence of fast changing video frames. Wecompare our hybrid
approach framework’s simulation results with different resolution enhancement techniques i.e. Robust Super-resolution, IBP and Interpolation methods reported in the literature. This
approach shows good results in term of different quality parameters.
In this technical article, we present a Novel algorithm for the lossy compression method, where the performance and storage has been proscribed with hardware descriptive language (HDL).
Stereo vision-based obstacle avoidance module on 3D point cloud dataTELKOMNIKA JOURNAL
This paper deals in building a 3D vision-based obstacle avoidance and navigation. In order for an autonomous system to work in real life condition, a capability of gaining surrounding environment data, interpret the data and take appropriate action is needed. One of the required capability in this matter for an autonomous system is a capability to navigate cluttered, unorganized environment and avoiding collision with any present obstacle, defined as any data with vertical orientation and able to take decision when environment update exist. Proposed in this work are two-step strategy of extracting the obstacle position and orientation from point cloud data using plane based segmentation and the resultant segmentation are mapped based on obstacle point position relative to camera using occupancy grid map to acquire obstacle cluster position and recorded the occupancy grid map for future use and global navigation, obstacle position gained in grid map is used to plan the navigation path towards target goal without going through obstacle position and modify the navigation path to avoid collision when environment update is present or platform movement is not aligned with navigation path based on timed elastic band method.
A Novel Mechanism for Low Bit-Rate CompressionIOSR Journals
Abstract: Sparse sampling techniques have been around in digital photography. In this approach compression follows oversampling. In this paper a uniform down sampling is practically implemented. Moreover it supports adaptive sampling with low-pass and varying pre-filtering. The result of this can be compressed and then sent across to destination without making changes to current image. A decoder is built in MATLAB which decompresses image using the low-pass pre-filtering approach. The proposed approach is known as adaptive down sampling and up conversion which is far better than JPEG 2000. The prototype application is built to evaluate this fact. The proposed system exhibited low-bit rates with higher visual quality. The results revealed that the proposed method can be used in real world applications. Index Terms–Image processing, up conversion, pre-filtering, and adaptive sampling.
Tissue Segmentation Methods Using 2D Histogram Matching in a Sequence of MR B...Vladimir Kanchev
This presentation provides detailed description of the methodology of the segmentation method of brain tissues in MR image sequences using 2D histogram matching.
Tissue Segmentation Methods using 2D Hiistogram Matching in a Sequence of MR ...Vladimir Kanchev
Methodology of the suggested method for tissue segmentation in MR brain images using 2D histogram matching. Each algorithmic step is given in detail and analyzed.
COM2304: Introduction to Computer Vision & Image Processing Hemantha Kulathilake
At the end of this lesson, you should be able to;
Describe image.
Describe digital image processing and computer vision.
Compare and Contrast image processing and computer vision.
Describe image sources.
Identify the array of imaging application under the EM Image source.
Describe the components of Image processing system and computer vision system.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
A REGULARIZED ROBUST SUPER-RESOLUTION APPROACH FORALIASED IMAGES AND LOW RESO...cscpconf
This paper presents a hybrid approach for images and video super-resolution. We have proposed the approach for enhancing the resolution of images and low resolution, under
sampled videos. We exploited the shift and motion based robust super-resolution (SR)algorithm [1] and the diffusion image regularization method proposed in [2] to obtain the alias free and jerk free smooth SR image.We presented a framework for obtaining super-resolution video thatis robust,even in the presence of fast changing video frames. Wecompare our hybrid
approach framework’s simulation results with different resolution enhancement techniques i.e. Robust Super-resolution, IBP and Interpolation methods reported in the literature. This
approach shows good results in term of different quality parameters.
In this technical article, we present a Novel algorithm for the lossy compression method, where the performance and storage has been proscribed with hardware descriptive language (HDL).
Stereo vision-based obstacle avoidance module on 3D point cloud dataTELKOMNIKA JOURNAL
This paper deals in building a 3D vision-based obstacle avoidance and navigation. In order for an autonomous system to work in real life condition, a capability of gaining surrounding environment data, interpret the data and take appropriate action is needed. One of the required capability in this matter for an autonomous system is a capability to navigate cluttered, unorganized environment and avoiding collision with any present obstacle, defined as any data with vertical orientation and able to take decision when environment update exist. Proposed in this work are two-step strategy of extracting the obstacle position and orientation from point cloud data using plane based segmentation and the resultant segmentation are mapped based on obstacle point position relative to camera using occupancy grid map to acquire obstacle cluster position and recorded the occupancy grid map for future use and global navigation, obstacle position gained in grid map is used to plan the navigation path towards target goal without going through obstacle position and modify the navigation path to avoid collision when environment update is present or platform movement is not aligned with navigation path based on timed elastic band method.
A Novel Mechanism for Low Bit-Rate CompressionIOSR Journals
Abstract: Sparse sampling techniques have been around in digital photography. In this approach compression follows oversampling. In this paper a uniform down sampling is practically implemented. Moreover it supports adaptive sampling with low-pass and varying pre-filtering. The result of this can be compressed and then sent across to destination without making changes to current image. A decoder is built in MATLAB which decompresses image using the low-pass pre-filtering approach. The proposed approach is known as adaptive down sampling and up conversion which is far better than JPEG 2000. The prototype application is built to evaluate this fact. The proposed system exhibited low-bit rates with higher visual quality. The results revealed that the proposed method can be used in real world applications. Index Terms–Image processing, up conversion, pre-filtering, and adaptive sampling.
Tissue Segmentation Methods Using 2D Histogram Matching in a Sequence of MR B...Vladimir Kanchev
This presentation provides detailed description of the methodology of the segmentation method of brain tissues in MR image sequences using 2D histogram matching.
Tissue Segmentation Methods using 2D Hiistogram Matching in a Sequence of MR ...Vladimir Kanchev
Methodology of the suggested method for tissue segmentation in MR brain images using 2D histogram matching. Each algorithmic step is given in detail and analyzed.
COM2304: Introduction to Computer Vision & Image Processing Hemantha Kulathilake
At the end of this lesson, you should be able to;
Describe image.
Describe digital image processing and computer vision.
Compare and Contrast image processing and computer vision.
Describe image sources.
Identify the array of imaging application under the EM Image source.
Describe the components of Image processing system and computer vision system.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
JAVA 2013 IEEE IMAGEPROCESSING PROJECT Reversible data hiding with optimal va...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
MULTIPLE CAUSAL WINDOW BASED REVERSIBLE DATA EMBEDDINGijistjournal
Reversible data embedding is a technique that embeds data into an image in a reversible manner. An important aspect of reversible data embedding is to find embedding area in the image and to embed the data into it. In the conventional reversible techniques, the visual quality is not taken into account which resulted in a poor quality of the embedded images. Hence the histogram modification based reversible data hiding technique using multiple causal windows is proposed which predicts the embedding level with the help of the pixel value, edge value, Just Noticeable Difference(JND) value. Using this data embedding level the data is embedded into the pixels. The pixel level adjustment considering the Human Visual System (HVS) characteristics is also made to reduce the distortion caused by data embedding. This significantly improves the data embedding capacity along with greater visual quality. The proposed method includes three phases: (i).Construction of casual window and calculation of edge and JND values in which the casual window determines the pixel values, the edge and the JND values are calculated (ii).Data embedding which is the process of embedding the data into the original image (iii). Data extractor and image recovery where the original image is recovered and the embedded bits are obtained. The experimental results and performance comparison with other reversible data hiding algorithms are presented to demonstrate the validity of the proposed algorithm. The experimental results show that the Performance of the proposed system on an average shows an accuracy of 95%.
MULTIPLE CAUSAL WINDOW BASED REVERSIBLE DATA EMBEDDINGijistjournal
Reversible data embedding is a technique that embeds data into an image in a reversible manner. An important aspect of reversible data embedding is to find embedding area in the image and to embed the data into it. In the conventional reversible techniques, the visual quality is not taken into account which resulted in a poor quality of the embedded images. Hence the histogram modification based reversible data hiding technique using multiple causal windows is proposed which predicts the embedding level with the help of the pixel value, edge value, Just Noticeable Difference(JND) value. Using this data embedding level the data is embedded into the pixels. The pixel level adjustment considering the Human Visual System (HVS) characteristics is also made to reduce the distortion caused by data embedding. This significantly improves the data embedding capacity along with greater visual quality. The proposed method includes three phases: (i).Construction of casual window and calculation of edge and JND values in which the casual window determines the pixel values, the edge and the JND values are calculated (ii).Data embedding which is the process of embedding the data into the original image (iii). Data extractor and image recovery where the original image is recovered and the embedded bits are obtained. The experimental results and performance comparison with other reversible data hiding algorithms are presented to demonstrate the validity of the proposed algorithm. The experimental results show that the Performance of the proposed system on an average shows an accuracy of 95%.
A Novel Approach to Image Denoising and Image in PaintingEswar Publications
Image denoising is an important image processing task, both as a process itself, and as a component in other processes. Very many ways to denoise an image or a set of data exists. The main properties of a good image denoising model are that it will remove noise while preserving edges. Traditionally, linear models have been used. One common approach is to use a Gaussian filter, or equivalently solving the heat-equation with the noisy image as input-data, i.e. a linear, 2nd order PDE-model. For some purposes this kind of denoising is adequate. One big advantage of linear noise removal models is the speed. But a back draw of the linear models is that they are not
able to preserve edges in a good manner: edges, which are recognized as discontinuities in the image, are smeared out. Here I am using a novel approach to image denoising that is level set approach is employed. Level Set Methods offer an appealing approach to noise removal. In particular, they exploit the fact that curves moving under their curvature smooth out and disappear. Since the method evolves contours, boundaries remain essentially sharp and do not blur. Second, a "min/max" switch is used to control whether or not curvature flow is applied; this results in an algorithm that stops automatically once the smallest features are removed.
A Smart Camera Processing Pipeline for Image Applications Utilizing Marching ...sipij
Image processing in machine vision is a challenging task because often real-time requirements have to be met in these systems. To accelerate the processing tasks in machine vision and to reduce data transfer latencies, new architectures for embedded systems in intelligent cameras are required. Furthermore, innovative processing approaches are necessary to realize these architectures efficiently. Marching Pixels are such a processing scheme, based on Organic Computing principles, and can be applied for example to determine object centroids in binary or gray-scale images. In this paper, we present a processing pipeline for smart camera systems utilizing such Marching Pixel algorithms. It consists of a buffering template for image pre-processing tasks in a FPGA to enhance captured images and an ASIC for the efficient realization of Marching Pixel approaches. The ASIC achieves a speedup of eight for the realization of Marching Pixel algorithms, compared to a common medium performance DSP platform.
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.
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JPEEE1440 Cascaded Two-Level Inverter-Based Multilevel STATCOM for High-Pow...chennaijp
We offer different types of eee projects at affordable price in Chennai. You can easily choose titles with abstract and also full base paper for your reference.
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JPN1423 Stars a Statistical Traffic Patternchennaijp
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JPN1422 Defending Against Collaborative Attacks by Malicious Nodes in MANETs...chennaijp
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JPN1417 AASR: An Authenticated Anonymous Secure Routing Protocol for MANETs ...chennaijp
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JP INFOTECH is one of the leading Matlab projects provider in Chennai having experience faculties. We have list of image processing projects as our own and also we can make projects based on your own base paper concept also.
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JPM1407 Exposing Digital Image Forgeries by Illumination Color Classificationchennaijp
JP INFOTECH is one of the leading Matlab projects provider in Chennai having experience faculties. We have list of image processing projects as our own and also we can make projects based on your own base paper concept also.
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Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
JPM1416 A Unified Data Embedding and Scrambling Method
1. A Unified Data Embedding and Scrambling Method
ABSTRACT:
Conventionally, data embedding techniques aim at maintaining high-output image
quality so that the difference between the original and the embedded images is
imperceptible to the naked eye. Recently, as a new trend, some researchers
exploited reversible data embedding techniques to deliberately degrade image
quality to a desirable level of distortion. In this paper, a unified data embedding-scrambling
technique called UES is proposed to achieve two objectives
simultaneously, namely, high payload and adaptive scalable quality degradation.
First, a pixel intensity value prediction method called checkerboard-based
prediction is proposed to accurately predict 75% of the pixels in the image based
on the information obtained from 25% of the image. Then, the locations of the
predicted pixels are vacated to embed information while degrading the image
quality. Given a desirable quality (quantified in SSIM) for the output image, UES
guides the embedding-scrambling algorithm to handle the exact number of pixels,
i.e., the perceptual quality of
the embedded-scrambled image can be controlled. In addition, the prediction errors
are stored at a predetermined precision using the structure side information to
2. perfectly reconstruct or approximate the original image. In particular, given a
desirable SSIM value, the precision of the stored prediction errors can be adjusted
to control the perceptual quality of the reconstructed image. Experimental results
confirmed that UES is able to perfectly reconstruct or approximate the original
image with SSIM value >0.99 after completely degrading its perceptual quality
while embedding at 7.001bpp on average.
EXISTING SYSTEM:
Data embedding methods can be further classified into two main categories,
namely, irreversible and reversible. Conventionally, both irreversible and
reversible embedding techniques try to maintain the perceptual quality of the
output image (i.e., embedded with data) at the highest possible level while
embedding as many external information as possible into the image. For
irreversible techniques, the loss of information due to the embedding process is
permanent and the original image is not completely recoverable. For reversible
methods, in addition to above mentioned objectives, the method must be able to
perfectly reconstruct the original image. Reversibility is an attractive and beneficial
feature particularly for those applications dealing with crucial and sensitive
information such as medical images, military images, forensic, and valuable
artwork.
3. DISADVANTAGES OF EXISTING SYSTEM:
joint approach should be able to severely degrade the perceptual
quality of the image by embedding external information into it while
being able to reconstruct the original content.
due to the huge number of modifications in the structure of the
original content, the reconstruction process is more technically
challenging in the joint approach when compared to that of the
conventional data embedding methods.
PROPOSED SYSTEM:
In this work, a novel unified data embedding and scrambling (UES) method is
proposed to degrade image quality of an image by inserting external information
into it. Instead of transforming to new domain (such as Universal Domain) or
finding some features suitable for data embedding, external information are
inserted into selected pixel locations by direct replacement. Pixel intensity values
are first predicted by using the proposed novel prediction method, and then the
4. selected locations among the predicted pixels are vacated and replaced by the
external information.
ADVANTAGES OF PROPOSED SYSTEM:
Given a desirable SSIM value, UES is able to control the distortion of the
output image to the targeted level.
UES can operate in two modes, namely, lossless to allow perfect restoration
of the original host image, or lossy to accommodate high payload.
5. SYSTEM ARCHITECTURE:
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 1.44 Mb.
6. Monitor : 15 VGA Colour.
Mouse : Logitech.
Ram : 512 Mb.
SOFTWARE REQUIREMENTS:
Operating system : Windows XP/7.
Coding Language : MATLAB
Tool : MATLAB R 2007B
REFERENCE:
Reza Moradi Rad, Student Member, IEEE, KokSheik Wong, Member, IEEE, and
Jing-Ming Guo, Senior Member, IEEE ,“A Unified Data Embedding and
Scrambling Method”, IEEE TRANSACTIONS ON IMAGE PROCESSING,
VOL. 23, NO. 4, APRIL 2014.
