For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
The document summarizes an adaptive image steganography technique that embeds secret messages into digital images. It proposes using adaptive quantization embedding, where quantization steps for image blocks are optimized to guarantee more data can be embedded in busy image areas with high contrast. The technique embeds adaptive quantization parameters and message bits into the cover image using a difference expanding algorithm. Simulation results showed the proposed scheme can provide a good balance between imperceptibility and embedding capacity.
The Image Quilting algorithm synthesizes new textures by taking patches from a sample texture and arranging them to match on overlapping regions, minimizing errors. It works on both stochastic and repeated textures. Patches are selected randomly from the sample but placed to match overlapping regions. A minimum error boundary cut is calculated between patches using dynamic programming. Parameters like patch size and overlap affect quality and speed. The algorithm generates realistic new textures but has room for improved blending and faster search methods.
Our approach for steganography uses reversible texture synthesis to conceal secret messages. A smaller source texture is resampled to synthesize a new texture image of arbitrary size, embedding messages during this process. This allows extraction of both the secret messages and original source texture from the synthesized stego texture. Our scheme offers variable embedding capacity proportional to the stego texture size, resistance to steganalysis, and reversible recovery of the source texture.
The document discusses and compares different steganographic algorithms and steganalysis techniques. It defines steganography and steganalysis, describing various steganographic schemes like LSB embedding, Outguess, F5, and Model-based steganography. It also covers past and modern work in steganalysis, including statistical methods for detecting hidden messages. The document concludes by discussing the future of steganography and its potential limitations under laws.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
The document summarizes an adaptive image steganography technique that embeds secret messages into digital images. It proposes using adaptive quantization embedding, where quantization steps for image blocks are optimized to guarantee more data can be embedded in busy image areas with high contrast. The technique embeds adaptive quantization parameters and message bits into the cover image using a difference expanding algorithm. Simulation results showed the proposed scheme can provide a good balance between imperceptibility and embedding capacity.
The Image Quilting algorithm synthesizes new textures by taking patches from a sample texture and arranging them to match on overlapping regions, minimizing errors. It works on both stochastic and repeated textures. Patches are selected randomly from the sample but placed to match overlapping regions. A minimum error boundary cut is calculated between patches using dynamic programming. Parameters like patch size and overlap affect quality and speed. The algorithm generates realistic new textures but has room for improved blending and faster search methods.
Our approach for steganography uses reversible texture synthesis to conceal secret messages. A smaller source texture is resampled to synthesize a new texture image of arbitrary size, embedding messages during this process. This allows extraction of both the secret messages and original source texture from the synthesized stego texture. Our scheme offers variable embedding capacity proportional to the stego texture size, resistance to steganalysis, and reversible recovery of the source texture.
The document discusses and compares different steganographic algorithms and steganalysis techniques. It defines steganography and steganalysis, describing various steganographic schemes like LSB embedding, Outguess, F5, and Model-based steganography. It also covers past and modern work in steganalysis, including statistical methods for detecting hidden messages. The document concludes by discussing the future of steganography and its potential limitations under laws.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document provides information on several 2015 IEEE Matlab projects related to signal processing and image analysis. It lists the project titles, languages, links, and abstracts for 10 different Matlab projects. The projects cover topics such as target source separation using deep neural networks, hyperspectral image classification using sparse representation, image denoising techniques, and cardiovascular biometrics.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document describes six MATLAB projects available from VenSoft Technologies for the 2014-2015 academic year. It provides the titles, abstracts, publishing details, and index terms for each project. The projects involve topics such as sparse unmixing of hyperspectral data, mixed noise removal, subspace matching pursuit, exploiting spectral a priori information, gradient histogram preservation for image denoising, and image set-based collaborative representation for face recognition.
Background context augmented hypothesis graph for object segmentationI3E Technologies
This paper addresses semantic segmentation by using an augmented hypothesis graph with contextual information. It mines background information from a training set and applies it to the unary terms of foreground regions in a fully connected conditional random field model over overlapping segment hypotheses. The final segmentation is obtained through maximum a posteriori inference followed by post-processing steps. Experimental results on PASCAL VOC 2012 and MSRC-21 data sets show the approach achieves state-of-the-art performance by incorporating contextual cues such as image classification and object detection.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Steganography Using Reversible Texture Synthesis1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Automatic dynamic focusing through interfaces (abstract)Jose Miguel Moreno
This document presents a new approach to automatic dynamic focusing through interfaces in non-destructive testing. The approach converts the two propagation media scenario into a single homogeneous medium, allowing for faster computation of focal laws. It then uses a specialized focusing hardware initialized with a few values to perform dynamic focusing at all output samples in real-time, avoiding the need for intensive iterative computations. Experimental results show the technique achieves small enough focusing errors to validate its use across many applications, with resolution and dynamic range almost unaffected compared to conventional offline computation methods. It significantly reduces both computation time and storage requirements for the testing equipment.
IEEE PROJECT TOPICS &ABSTRACTS on image processingaswin tbbc
The document describes a proposed approach called Multiview Alignment Hashing (MAH) for learning image hashing functions from multiple feature representations. Existing hashing methods rely on a single feature descriptor and spectral or graph-based techniques. MAH uses Nonnegative Matrix Factorization to combine multiple views, finding a low-dimensional representation that respects the joint probability distribution of data views while discarding redundancy. It formulates the problem as non-convex optimization and solves it through alternate optimization. Evaluation on image datasets shows MAH outperforms state-of-the-art multiview hashing techniques.
This document describes a new lossless color image compression algorithm based on hierarchical prediction and context-adaptive arithmetic coding. It decorrelates RGB images using a reversible color transform, then encodes the Y component conventionally and the chrominance components hierarchically using upper, left, and lower pixels for prediction rather than just upper and left. An appropriate context model is defined for prediction errors, which are arithmetic coded. Testing showed this method achieves better bit rate compression than JPEG2000 and JPEG-XR.
Cross layer design of congestion control and power control in fast-fading wir...Ecway Technologies
This document proposes three algorithms for cross-layer design of congestion control and power control in wireless networks. The first algorithm uses complete convexification to achieve global optimal source rates and link power allocation in a distributed manner but requires large messages. The second algorithm uses outage probability bounds to map to an SIR constraint and develop a near-optimal distributed algorithm using local SIR measurements. The third algorithm uses successive convex approximation to iteratively transform the nonconvex problem into convex problems and achieve distributed optimal solutions. Numerical results show the algorithms perform similarly while the second algorithm converges faster, making it more practical.
ON THE IMAGE QUALITY AND ENCODING TIMES OF LSB, MSB AND COMBINED LSB-MSBijcsit
The Least Significant Bit (LSB) algorithm and the Most Significant Bit (MSB) algorithm are stenography algorithms with each one having its demerits. This work therefore proposed a Hybrid approach and compared its efficiency with LSB and MSB algorithms. The Least Significant Bit (LSB) and Most
Significant Bit (MSB) techniques were combined in the proposed algorithm. Two bits (the least significant bit and the most significant bit) of the cover images were replaced with a secret message. Comparisons were made based on Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and the encoding time between the proposed algorithm, LSB and MSB after embedding in digital images. The combined
technique produced a stego-image with minimal distortion in image quality than MSB technique independent of the nature of data that was hidden. However, LSB algorithm produced the best stego-image quality. Large cover images however made the combined algorithm’s quality better improved. The combined algorithm had lesser time of image and text encoding. Therefore, a trade-off exists between the encoding time and the quality of stego-image as demonstrated in this work.
The document proposes a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. It integrates data hiding and image compression into a single module. On the sender side, residual blocks are embedded with secret data and compressed using SMVQ or image inpainting. The receiver can extract secret bits and decompress the image using the index values in segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.
This document provides information on several remote sensing projects from IEEE 2015. It lists the titles, languages, and abstracts for 8 projects related to classification and analysis of hyperspectral and multispectral images. The projects focus on techniques such as sparse representation in tangent space, Gabor feature-based collaborative representation, level set evolutions for object extraction, and dimension reduction using spatial and spectral regularization.
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Adaptive block-based pixel value differencing steganographyOsama Hosam
Steganography is the science of hiding secure data in digital carriers such as images and videos. Pixel value differencing
(PVD) steganography algorithms embed data into images depending on pixel neighborhood differences. We have pro-
posed PVD scheme for embedding secure data into digital images. The image is divided into non-overlapping 33 blocks.
The block’s median pixel is used as a reference for calculating pixel differences. The distance between the minimum and
maximum differences are fine tuned for spreading the secure data on a wide range of image regions with high-intensity
fluctuations. The embedding procedure embeds secure data into the content regions with edges and intensity transitions.
Texture images provide higher embedding size compared with regular images. The results showed that the proposed
algorithm is successfully able to avoid smooth regions in the embedding process. In addition, the proposed algorithm
shows better embedding quality compared with the state of the art PVD approaches especially with low-embedding rates.
This document provides information on several 2015 IEEE Matlab projects related to signal processing and image analysis. It lists the project titles, languages, links, and abstracts for 10 different Matlab projects. The projects cover topics such as target source separation using deep neural networks, hyperspectral image classification using sparse representation, image denoising techniques, and cardiovascular biometrics.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document describes six MATLAB projects available from VenSoft Technologies for the 2014-2015 academic year. It provides the titles, abstracts, publishing details, and index terms for each project. The projects involve topics such as sparse unmixing of hyperspectral data, mixed noise removal, subspace matching pursuit, exploiting spectral a priori information, gradient histogram preservation for image denoising, and image set-based collaborative representation for face recognition.
Background context augmented hypothesis graph for object segmentationI3E Technologies
This paper addresses semantic segmentation by using an augmented hypothesis graph with contextual information. It mines background information from a training set and applies it to the unary terms of foreground regions in a fully connected conditional random field model over overlapping segment hypotheses. The final segmentation is obtained through maximum a posteriori inference followed by post-processing steps. Experimental results on PASCAL VOC 2012 and MSRC-21 data sets show the approach achieves state-of-the-art performance by incorporating contextual cues such as image classification and object detection.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Steganography Using Reversible Texture Synthesis1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Automatic dynamic focusing through interfaces (abstract)Jose Miguel Moreno
This document presents a new approach to automatic dynamic focusing through interfaces in non-destructive testing. The approach converts the two propagation media scenario into a single homogeneous medium, allowing for faster computation of focal laws. It then uses a specialized focusing hardware initialized with a few values to perform dynamic focusing at all output samples in real-time, avoiding the need for intensive iterative computations. Experimental results show the technique achieves small enough focusing errors to validate its use across many applications, with resolution and dynamic range almost unaffected compared to conventional offline computation methods. It significantly reduces both computation time and storage requirements for the testing equipment.
IEEE PROJECT TOPICS &ABSTRACTS on image processingaswin tbbc
The document describes a proposed approach called Multiview Alignment Hashing (MAH) for learning image hashing functions from multiple feature representations. Existing hashing methods rely on a single feature descriptor and spectral or graph-based techniques. MAH uses Nonnegative Matrix Factorization to combine multiple views, finding a low-dimensional representation that respects the joint probability distribution of data views while discarding redundancy. It formulates the problem as non-convex optimization and solves it through alternate optimization. Evaluation on image datasets shows MAH outperforms state-of-the-art multiview hashing techniques.
This document describes a new lossless color image compression algorithm based on hierarchical prediction and context-adaptive arithmetic coding. It decorrelates RGB images using a reversible color transform, then encodes the Y component conventionally and the chrominance components hierarchically using upper, left, and lower pixels for prediction rather than just upper and left. An appropriate context model is defined for prediction errors, which are arithmetic coded. Testing showed this method achieves better bit rate compression than JPEG2000 and JPEG-XR.
Cross layer design of congestion control and power control in fast-fading wir...Ecway Technologies
This document proposes three algorithms for cross-layer design of congestion control and power control in wireless networks. The first algorithm uses complete convexification to achieve global optimal source rates and link power allocation in a distributed manner but requires large messages. The second algorithm uses outage probability bounds to map to an SIR constraint and develop a near-optimal distributed algorithm using local SIR measurements. The third algorithm uses successive convex approximation to iteratively transform the nonconvex problem into convex problems and achieve distributed optimal solutions. Numerical results show the algorithms perform similarly while the second algorithm converges faster, making it more practical.
ON THE IMAGE QUALITY AND ENCODING TIMES OF LSB, MSB AND COMBINED LSB-MSBijcsit
The Least Significant Bit (LSB) algorithm and the Most Significant Bit (MSB) algorithm are stenography algorithms with each one having its demerits. This work therefore proposed a Hybrid approach and compared its efficiency with LSB and MSB algorithms. The Least Significant Bit (LSB) and Most
Significant Bit (MSB) techniques were combined in the proposed algorithm. Two bits (the least significant bit and the most significant bit) of the cover images were replaced with a secret message. Comparisons were made based on Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and the encoding time between the proposed algorithm, LSB and MSB after embedding in digital images. The combined
technique produced a stego-image with minimal distortion in image quality than MSB technique independent of the nature of data that was hidden. However, LSB algorithm produced the best stego-image quality. Large cover images however made the combined algorithm’s quality better improved. The combined algorithm had lesser time of image and text encoding. Therefore, a trade-off exists between the encoding time and the quality of stego-image as demonstrated in this work.
The document proposes a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. It integrates data hiding and image compression into a single module. On the sender side, residual blocks are embedded with secret data and compressed using SMVQ or image inpainting. The receiver can extract secret bits and decompress the image using the index values in segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.
This document provides information on several remote sensing projects from IEEE 2015. It lists the titles, languages, and abstracts for 8 projects related to classification and analysis of hyperspectral and multispectral images. The projects focus on techniques such as sparse representation in tangent space, Gabor feature-based collaborative representation, level set evolutions for object extraction, and dimension reduction using spatial and spectral regularization.
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Adaptive block-based pixel value differencing steganographyOsama Hosam
Steganography is the science of hiding secure data in digital carriers such as images and videos. Pixel value differencing
(PVD) steganography algorithms embed data into images depending on pixel neighborhood differences. We have pro-
posed PVD scheme for embedding secure data into digital images. The image is divided into non-overlapping 33 blocks.
The block’s median pixel is used as a reference for calculating pixel differences. The distance between the minimum and
maximum differences are fine tuned for spreading the secure data on a wide range of image regions with high-intensity
fluctuations. The embedding procedure embeds secure data into the content regions with edges and intensity transitions.
Texture images provide higher embedding size compared with regular images. The results showed that the proposed
algorithm is successfully able to avoid smooth regions in the embedding process. In addition, the proposed algorithm
shows better embedding quality compared with the state of the art PVD approaches especially with low-embedding rates.
AN ENHANCED EDGE ADAPTIVE STEGANOGRAPHY APPROACH USING THRESHOLD VALUE FOR RE...ijcsa
The document summarizes an enhanced edge adaptive steganography approach using a threshold value for region selection. It aims to improve the quality and modification rate of a stego image compared to Sobel and Canny edge detection techniques. The proposed approach uses a threshold value to select high frequency pixels from the cover image for data embedding using LSBMR. Experimental results on 100 images show about a 0.2-0.6% improvement in image quality measured by PSNR and a 4-10% improvement in modification rate measured by MSE compared to Sobel and Canny edge detection.
In this paper, a new steganography algorithm has been suggested to enforce the security of data hiding and to increase the amount of payloads. This algorithm is based on four safety layers; the first safety layer has been initiated through compression and an encryption of a confidential message using a set partition in hierarchical trees (SPIHT) and advanced encryption standard (AES) mechanisms respectively. An irregular image segmentation algorithm (IIS) on a cover-image (Ic) has been constructed successfully in
the second safety layer, and it is based on the adaptive reallocation segments' edges (ARSE) by applying an
adaptive finite-element method (AFEM) to find the numerical solution of the proposed partial differential equation (PDE). An intelligent computing technique using a hybrid adaptive neural network with a modified ant colony optimizer (ANN_MACO) has been proposed in the third safety layer to construct a
learning system. This system accepts entry using support vector machine (SVM) to generate input patterns as features of byte attributes and produces new features to modify a cover-image. The significant innovation of the proposed novel steganography algorithm is applied efficiently on the forth
safety layer which is more robust for hiding a large amount of confidential message reach to six bits per pixel (bpp) into color images. The new approach of hiding algorithm works against statistical and visual attacks with high imperceptible of hiding data into stego-images (Is). The experimental results are
discussed and compared with the previous steganography algorithms; it demonstrates that the proposed algorithm has a significant improvement on the effect of the security level of steganography by making an arduous task of retrieving embedded confidential message from color images.
IMPROVED STEGANOGRAPHIC SECURITY BY APPLYING AN IRREGULAR IMAGE SEGMENTATION ...IJNSA Journal
In this paper, a new steganography algorithm has been suggested to enforce the security of data hiding and to increase the amount of payloads. This algorithm is based on four safety layers; the first safety layer has been initiated through compression and an encryption of a confidential message using a set partition in hierarchical trees (SPIHT) and advanced encryption standard (AES) mechanisms respectively. An irregular image segmentation algorithm (IIS) on a cover-image (Ic) has been constructed successfully in the second safety layer, and it is based on the adaptive reallocation segments' edges (ARSE) by applying an adaptive finite-element method (AFEM) to find the numerical solution of the proposed partial differential equation (PDE). An intelligent computing technique using a hybrid adaptive neural network with a modified ant colony optimizer (ANN_MACO) has been proposed in the third safety layer to construct a learning system. This system accepts entry using support vector machine (SVM) to generate input patterns as features of byte attributes and produces new features to modify a cover-image.
The significant innovation of the proposed novel steganography algorithm is applied efficiently on the forth safety layer which is more robust for hiding a large amount of confidential message reach to six bits per pixel (bpp) into color images. The new approach of hiding algorithm works against statistical and visual attacks with high imperceptible of hiding data into stego-images (Is). The experimental results are discussed and compared with the previous steganography algorithms; it demonstrates that the proposed algorithm has a significant improvement on the effect of the security level of steganography by making an arduous task of retrieving embedded confidential message from color images.
A PROJECT REPORT ON REMOVAL OF UNNECESSARY OBJECTS FROM PHOTOS USING MASKINGIRJET Journal
This document presents a project report on removing unnecessary objects from photos using masking techniques. It discusses using algorithms like Fast Marching and Navier-Stokes to fill in missing image data and maintain continuity across boundaries. The Fast Marching method begins at region boundaries and works inward, prioritizing completion of boundary pixels first. Navier-Stokes uses fluid dynamics equations to continue intensity value functions and ensure they remain continuous at boundaries. Color filtering can also be used to segment specific colored objects or regions. The project aims to implement these techniques to remove unwanted objects from images and fill the resulting gaps seamlessly.
This document contains information about 36 MATLAB projects related to digital image processing and communications. It includes the project codes, titles, and descriptions. The projects cover topics like image recognition, biometrics, medical imaging, steganography, watermarking, and more. It also provides contact information for the company that developed these projects.
In this paper, we propose a new method of non-adaptive LSB steganography in still images to
improve the embedding efficiency from 2 to 8/3 random bits per one embedding change even for
the embedding rate of 1 bit per pixel. The method takes 2-bits of the secret message at a time
and compares them to the LSBs of the two chosen pixel values for embedding, it always assumes
a single mismatch between the two and uses the second LSB of the first pixel value to hold the
index of the mismatch. It is shown that the proposed method outperforms the security of LSB
replacement, LSB matching, and LSB matching revisited by reducing the probability of
detection with their current targeted steganalysis methods. Other advantages of the proposed
method are reducing the overall bit-level changes to the cover image for the same amount of
embedded data and avoiding complex calculations. Finally, the new method results in little
additional distortion in the stego image, which could be tolerated.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document discusses efficient rendezvous algorithms for wireless sensor networks with mobile base stations. It proposes an approach where select sensor nodes act as rendezvous points, buffering and aggregating data from other sensors. These rendezvous points then transfer the collected data to the base station when it arrives, combining the advantages of controlled mobility and in-network caching. Algorithms are presented for rendezvous design with mobile base stations having variable or fixed tracks. Both theoretical analysis and simulations validate that this approach can achieve a good balance between energy savings and reduced data collection latency in the network.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document discusses preventing private information inference attacks on social networks. It explores how released social networking data could be used to predict undisclosed private information about individuals, such as their political affiliation or sexual orientation. It then describes three sanitization techniques that could be used to decrease the effectiveness of such attacks. An experiment is conducted applying these techniques to a Facebook dataset to attempt to discover sensitive attributes through collective inference and show that the sanitization methods decrease the effectiveness of local and relational classification algorithms.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
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Slideshare: http://www.slideshare.net/PECBCERTIFICATION
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
1. Impulse Technologies
Beacons U to World of technology
044-42133143, 98401 03301,9841091117 ieeeprojects@yahoo.com www.impulse.net.in
Targeted Steganalysis of Edge Adaptive Image Steganography
Based on LSB Matching Revisited Using B-Spline Fitting
Abstract
In this letter, the authors point out that the readjusting phase of edge adaptive
image steganography based on LSB matching revisited introduces a pulse distortion to
the long exponential tail of the histogram of the absolute difference of the pixel pairs.
Making use of this observation, a targeted steganalytic method based on B-Spline fitting
is proposed. Experimental results show that the proposed method obtains excellent results
for detecting stego images with low embedding rate. The dominant performance of our
method compared with state-of-the-art blind steganalyzers, such as SPAM and SRM is
apparent. Furthermore, our method can accurately estimate the threshold used in the
secret data embedding procedure and can separate the stego images with unit block size
from those with block sizes greater than one.
Your Own Ideas or Any project from any company can be Implemented
at Better price (All Projects can be done in Java or DotNet whichever the student wants)
1