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Design and Implementation of 8-Bit vedic Multiplier Using Cadence 45nm Technology

Design and Implementation of 8-Bit Vedic Multiplier Using Ca...

引用

Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International conference on

作者： v. Sharmila vandanapu Saikumar G. C. Pranav Sai Subhash Naigapula Rakesh Shaik Bilaal Department of Electronics and Communication Engineering Vignana Bharathi Institute of Technology Gathkesar Telangana India

In modern digital signal processing and various other applications, multipliers serve as fundamental components within high-speed arithmetic logic units, microcomputers, and image processing systems. It’s important to note that the multiplication process typically demands greater hardware resources and computation time compared to addition and subtraction processes. Several algorithms have initiated to implement fast multiplier. In this algorithms vEDIC Multiplication is one of the method to implement efficient multiplier. vedic mathematics offers a set of sixteen sutras or techniques for mathematical calculations, with one of the most commonly used ones being "Urdhva-Triyagbhyam," which translates to “vertically and Crosswise.” This technique has been adapted and refined to enhance its efficiency in multiplication. It serves as a universal multiplication formula, applicable to various scenarios. When using the vedic multiplier technique, the multiplication of two numbers involves applying the vertically and Crosswise approach and then summing up the results. What makes “Urdhva Triyagbhyam” particularly valuable is its ability to deliver fast multiplication results, regardless of the size or type of numbers being multiplied. It minimizes the delay in the multiplication process, making it a highly efficient algorithm for all multiplication cases. It also provides the power optimization.

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Adversarial Attacks For Multi Target image Translation Networks

Adversarial Attacks For Multi Target Image Translation Netwo...

引用

Symposium of image, signal processing, and Artificial vision (STSIvA)

作者： Zigang Fang Yu Yang Jialin Lin Rui Zhan School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

Although image translation algorithms such as StarGAN, STGAN, StarGAN-v2, etc. based on the generative adversarial networks, bring enormous convenience to people's work and life, they also have greater security risks in terms of privacy and security ethics. We tackle this problem of generating adversarial attacks against image translation models, which disrupt the resulting output image. The existing adversarial technology can only generate adversarial samples for a single image translation model, but in actual applications, it is unknown to the user which model an attacker will use. The paper draws on the idea of multi-task learning and proposes a multi-objective adversarial sample generation algorithm to generate images that can simultaneously defend against tampering with multiple state- of-the-art image translation models. The simulation result shows that compared with the original images, adversarial images have no heavy visual distortion with PSNR of 27.17dB and SSIM of 0.70 which means that normal usages of images, such as showing something interesting, amazing, funny, cool or etc., are not affected. The adversarial samples generated by our proposed algorithm reduce the risk of malicious tampering and abuse of images. For the mainstream image translation models StarGAN, STGAN and StarGAN-v2, the attack success rates of the adversarial images generated by the algorithm are 100%, 66.67%, and 73.33%, respectively. It can be seen that the algorithm in this paper has obvious effects on protecting the reasonable and safe use of multimedia resources on social platforms.

关键词： visualization Privacy Simulation Distortion Security Informatics Strain

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Removal of Gaussian Noise from Stationary image using Shift Invariant wavelet Transform

Removal of Gaussian Noise from Stationary Image using Shift ...

引用

International conference on Wireless and Optical Communications Networks

作者： vikas Gupta Rajesh Mahle Ashish Shukla H.O.D. of ECE Dept. TIT Rajiv Gandhi Technical University Bhopal M.P. India ECE Dept. TIT Rajiv Gandhi Technical University Bhopal M.P. India

ISBN: (纸本)9781467359986

Discrete wavelet transform (DWT) has gained widespread recognition and popularity in image processing due to its ability of capturing energy of signal in a few energy transform value. As well as it has also ability to underline and represent time-varying spectral properties of many transient and other nonstationary signals. In DWT denoising is done only in detail coefficient, this offer advantage of smoothness and adaption. However DWT has a lack of shift invariance. This shift-variance is a major problem with the use of DWT for transient signal analysis and pattern recognition applications. Denoising of images with the DWT some time also give visual artifacts due to Gibbs phenomena in neighbourhood of discontinuities. In this paper, a shift-invariant analysis scheme is proposed for removing of additive Gaussian noise in stationary image. An investigation has been made on discrete wavelet transform with shift invariant in terms of PSNR and visual performance.

关键词： PSNR (Peak signal to noise ratio) DWT (Discrete wavelet transform) ε- Decimated Discrete wavelet Transform (ε- Decimated DWT) Shift Invariant wavelet transform

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Face Recognition Using Som Neural Network With Ddct Facial Feature Extraction Techniques

Face Recognition Using Som Neural Network With Ddct Facial F...

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International conference on Communications and signal processing

作者： Swati jadon Mahendra Kumar Yogesh Rathi the Department of computer science & Engineering YIT Jaipur India Department of Electronics & Communication Engineering University College of Engineering RTU Kota India.

ISBN: (纸本)9781479980826

This paper deals with 4 different techniques for feature extraction of image. Face detection is a necessary first-step in face recognition systems, with the purpose of localizing and extracting the face region from the background. The Self- Organizing Map (SOM) Neural Network has been used for training of database and simulation of FR system. The developed algorithm for the face recognition system formulates an image-based approach, using Directional discrete cosine transform (DDCT), discrete wavelet transform (DWT), discrete cosine transform (DCT) and Sobel edge detection, simulated in MATLAB. Simulation results are very promising.

关键词： Face Recognition (FR) Directional Discrete Cosine Transform (DDCT) Discrete Cosine Transform (DCT) Discrete wavelet Transform (DWT) Sobel Edge detection (SED) SOM Neural Network

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Decoding Complexity-Rate-Quality Pareto-Front for Adaptive vvC Streaming

Decoding Complexity-Rate-Quality Pareto-Front for Adaptive V...

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IEEE visual Communications and image processing (vCIP)

作者： Angeliki Katsenou vignesh v Menon Adam Wieckowski Benjamin Bross Detlev Marpe Bristol Digital Futures Institute University of Bristol UK Video Communication and Applications Department Fraunhofer HHI Berlin Germany

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

Pareto-front optimization is crucial for addressing the multi-objective challenges in video streaming, enabling the identification of optimal trade-offs between conflicting goals such as bitrate, video quality, and decoding complexity. This paper explores the construction of efficient bitrate ladders for adaptive versatile video Coding (vvC) streaming, focusing on optimizing these trade-offs. We investigate various ladder construction methods based on Pareto-front optimization, including exhaustive Rate-Quality and fixed ladder approaches. We propose a joint decoding time-rate-quality Pareto-front, providing a comprehensive framework to balance bitrate, decoding time, and video quality in video streaming. This allows streaming services to tailor their encoding strategies to meet specific requirements, prioritizing low decoding latency, bandwidth efficiency, or a balanced approach, thus enhancing the overall user experience. The experimental results confirm and demonstrate these opportunities for navigating the decoding time-rate-quality space to support various use cases. For example, when prioritizing low decoding latency, the proposed method achieves a decoding time reduction of 14.86 % while providing Bjøntegaard delta rate savings of 4.65 % and 0.32 dB improvement in the eXtended Peak signal-to-Noise Ratio (XPSNR)-Rate domain over the traditional fixed ladder solution.

关键词： video coding Runtime visual communication Bit rate Streaming media Decoding Quality assessment Complexity theory video recording Optimization

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Application Scenarios of Wireless Sensor Networks for Urban Transportation: a Survey

Application Scenarios of Wireless Sensor Networks for Urban ...

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第三十四届中国控制会议

作者： Xiaoya Hu Wei Xiong Wei Li Li Ke School of Automation Huazhong University of Science & Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control

ISBN: (纸本)9781467374439

The rapid progress in the research and development of electronics, sensing, signal processing, and communication networks has significantly advanced the state of applications of intelligent transportation systems(ITS). However, efficient and low-cost methods for gathering information in large-scale roads are lacking. Consequently, wireless sensor network(WSN) technologies that are low cost, low power, and self-configuring are a key function in ITS. The current state of the art of application scenarios of WSNs for urban transportation is captured in this paper, where solutions are discussed under their related application schemes. This paper also points out the potential application scenarios and design requirements of WSN for urban transportation.

关键词： WSN,ITS,urban transportation,application scenarios

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Automated Medical image Analyser

Automated Medical Image Analyser

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International conference on Communications and signal processing

作者： Moumita Bhowmik Dibyendu Ghoshal Susmita Bhowmik the National Institute of Technology Agartala Tripura India.

ISBN: (纸本)9781479980826

image segmentation plays an important role in the diagnosis of medical images. Medical image analysis is a very important topic for research as the process of diagnosis of diseases from the medical images becomes easier. Here, we have proposed a model of automated medical image identification based on fractal texture segmentation and corresponding image segmentation based on the test images and thus detecting the diseased part of the image. A new metric has been introduced for the segmentation of the image. The whole system being automated becomes less time consuming with respect to processing and transmission through channels. It is expected that proposed methodology would become reliable for the diagnosis of diseases. The integrated system designed can be used for healthcare applications and can find vast applications in other fields of medical science also.

关键词： Medical image segmentation morphological operators preprocessing automated system healthcare applications MATLAB

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wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Wavelet based Independent Component Analysis for Multispectr...

引用

International conference on Communication and signal processing

作者： Sindhumol S. Anil Kumar Kannan Balakrishnan Artificial Intelligence Lab Department of Computer Applications Cochin University of Science and Technology Kochi 682022 INDIA. Institute of Radiology and Imaging Sciences Indira Gandhi Co-operative Hospital Kochi 682020 INDIA Artificial Intelligence Lab Department of Computer Applications Cochin University of Science and Technology Kochi 682022 INDIA

ISBN: (纸本)9781467348652

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions.

关键词： Independent Component Analysis Magnetic Resonance Imaging Multispectral Analysis wavelet Transforms

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Local Smoothness Pattern for Content Based image Retrieval

Local Smoothness Pattern for Content Based Image Retrieval

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International conference on Communications and signal processing

作者： T.G. Subash Kumar v. Nagarajan Research scholar Faculty of Electrical and Electronics Department of ECE Sathyabama University is with Jasmin Infotech Private Ltd Chennai 600100 India Adhiparasakthi Engineering College Professor and Head Department of ECE Melmaruvathur 603319 India

ISBN: (纸本)9781479980826

Local binary pattern (LBP), which efficiently summarizes the local structure of images has been very successful in image retrieval applications. In this paper, we propose a Local Smoothness Pattern (LSP) for image retrieval applications which captures the smoothness over the curve directions in a local region. To compare its performance, this technique is applied to a database of 1180 sub-images from the twenty different classes of Brodatz database and is compared with the LBP. Result shows that the proposed technique achieves good retrieval rate.

关键词： Local Binary Pattern Local Smoothness Pattern image retrieval

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video Watermarking using Dyadic Filter and Discrete wavelet Transform

Video Watermarking using Dyadic Filter and Discrete Wavelet ...

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International conference on Wireless Communications, signal processing and Networking

作者： Dolley Shukla Manisha Sharma Dept. of Information Technology Shri Shankaracharya Technical Campus Bhilai India Dept. of Electronics & Telecommunication Bhilai Institute of Technology Durg India

ISBN: (纸本)9781467393393

The invisible watermark has many applications including video authentication, copy protection, broadcast monitoring, fingerprinting, enhanced video coding etc. Digital watermarking is a technology used for the copy protection of digital application. In this paper, a blind video watermarking scheme based on discrete wavelet transform (DWT) is proposed. 2-D DWT is performed in each frame of the original video. Then watermark embed into low frequency coefficients i.e. LL sub bands. Frequency sub divisions are performed by using Dyadic filter. To check effectiveness of the watermarked video, Peak signal to Noise Ratio, Mean Square Error, Normalized Mean Square, Absolute Mean Square Error parameters are used. The designed system's effectiveness is checked and tested using different wavelets.

关键词： Digital watermark video data Discrete wavelet Transform Frames Watermarking technique Copy protection

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