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Improved MDCFT-based Method for Estimating Physical Parameters from Newton's Rings 3

Improved MDCFT-Based Method for Estimating Physical Paramete...

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3rd international conference on Optics and image Processing, ICOIP 2023

作者： Shen, Deming Lu, Mingfeng Wu, Jinmin Xing, Ruoqi Xiong, Xiaoxin Wei, Hongtao Fan, Saihui Zhang, Feng Tao, Ran School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Fractional Signals and Systems Beijing100081 China School of Automation Beijing Information Science & Technology University Beijing100101 China

ISBN: (纸本)9781510667426

Newton's ring pattern is an typical interference fringe often encountered in optical measurements. The physical parameters, such as curvature radius, the ring's center can be estimated by analyzing it. Newton ring formed by spherical interference is two-dimensional Chirp signal, and its chirp parameters are almost impossible to be integers. However, the strict constraints of discrete Chirp Fourier transform (DCFT) and the existing discrete Modified Chirp Fourier transform (MDCFT) can only estimate the integer value part of parameter, which has a large recognition error. An improved MDCFT algorithm is proposed to further estimate the non-integer value part by using the object offset principle, thereby improving the estimation accuracy of Newton ring parameters. Experimental results verify the effectiveness and correctness of the proposed method. © 2023 SPIE. All rights reserved.

关键词： Parameter estimation

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Robust image Hashing based on Histogram Reconstruction 18th

Robust Image Hashing Based on Histogram Reconstruction

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18th international conference on Intelligent Information Hiding and Multimedia signal Processing, IIH-MSP 2022

作者： Jia, Yao Cui, Chen Wang, Zhenbang Tian, Shigang Wang, Shen School of Data Science and Technology Heilongjiang University Heilongjiang Harbin China College of Mathematics Physics and Information Engineering Jiaxing University Zhejiang Jiaxing China State Grid Heilongjiang Power Co. Ltd. Heilongjiang Harbin China School of Computer Science and Technology Harbin Institute of Technology Heilongjiang Harbin China

ISBN: (纸本)9789819906048

In this paper, we propose a perceptual image hashing method based on histogram reconstruction. Our method consists of three steps, pre-processing, histogram reconstruction and hash vector generation based on the reconstructed histogram. In image pre-processing, the color image is converted to a gray one, then the gray image is standardized and the standardized image is processed with a low-pass filter. Then, we reconstruct the histogram of a gray image by using the relationship between the pixels in different groups. Finally, the hash vector is extracted from the reconstructed histogram. As the experimental results show, the proposed image hashing method is robust to most of the content-preserving operations, such as JPEG compression, noise addition and rotation. Moreover, the method proposed can effectively solve the problems in traditional histogram-based methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Low pass filters

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Design and Implementation of Target Tracking System in Low Illumination Environment based on FPGA 2023

Design and Implementation of Target Tracking System in Low I...

引用

5th international Symposium on signal Processing systems, SSPS 2023

作者： Xin, Naijie Xie, Min Shi, Jian Lu, Tiantai Ma, Zhifeng School of Integrated Circuits and Electronics Beijing Institute of Technology China

ISBN: (纸本)9798400700040

Object tracking has been an important research topic in the field of computer vision. At present, most target tracking algorithms need to work in an environment with good lighting conditions. Environments such as night, rainy days, and foggy days will cause tracking drift and even target loss. In order to solve the above problems, this design proposes a target tracking system that combines image enhancement algorithm and target tracking algorithm. The image enhancement uses the Multi-Scale Retinex (MSR) algorithm to correct the color and dynamic range of the input image;the target tracking algorithm uses the Meanshift algorithm to track the enhanced image. In order to deploy the algorithm to FPGA for edge computing acceleration, a streaming computing architecture is designed, and at the same time, the algorithm is partially refactored at the design level to better adapt to FPGA deployment;finally, high-level synthesis tools are used, combined with optimization instructions A high-efficiency target tracking system with local parallelization and overall pipeline is designed. © 2023 ACM.

关键词： Field programmable gate arrays (FPGA)

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Face Super-Resolution Model based on Diffusion Model 1

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international conference on Communications, signal Processing, and systems, CSPS 2023

作者： Feng, Tianyi Xie, Yongping Dalian University of Technology Dalian116081 China

ISBN: (数字)9789819975020

ISBN: (纸本)9789819975556

The problem of restoring high-resolution images from blurry images has long been a concern, and traditional methods of directly interpolating low-resolution images to obtain high-resolution images are simple but ineffective. Inspired by SR3, we propose a super-resolution model of human faces based on the diffusion model, which achieves super-resolution through a random iterative denoising process. In this paper, we have used a residual block that integrates multi-scale spatial attention and coordinate attention. Additionally, we have enhanced the restoration of image details through a global attention model. These advancements effectively address the discrepancy between automated evaluation metrics and human perception in high-frequency details for super-resolution models. Through evaluation of the standard eight-fold super-resolution task on CelebA-HQ, our model performs well and achieves competitive scores on SSIM and PSNR metrics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Iterative methods

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A Comprehensive Study on BLE Enabled IoT based Tracking System (BITS) for Indoor Environment 2

A Comprehensive Study on BLE Enabled IoT Based Tracking Syst...

引用

2nd international conference on Intelligent Data Communication Technologies and internet of Things, IDCIoT 2024

作者： Roy, Pulakesh Mondal, Santu Biswas, Arindam Banerjee, Rajib Kazi Nazrul University Asansol Dept. of Mining Engineering West Bengal Asansol India Asansol Engineering College Dept. of Information Technology West Bengal Asansol India Centre of IoT and AI Integration with Education-Industry-Agriculture and Mining Engineering Kazi Nazrul University Asansol West Bengal Asansol India DR. B.C. Roy Engineering College Durgapur Dept. of Electronics and Communication Engineering West Bengal Durgapur India

ISBN: (纸本)9798350327533

With the development of the internet of Things (IoT) indoor location-aware applications have become a useful tool for locating objects in enclosed spaces. One of the most significant modern advances in IoT is Bluetooth Low Energy (BLE), which is especially suitable for extremely low-power sensors powered by CMOS coinage battery cells. With its reasonable accuracy and low-effort setup, BLE is a suitable application for indoor tracking systems. Intermittently, the BLE nodes send out messaging packets that contain the UUID (Universally Unique Identifier). In this research, an efficient tracking system has been designed for indoor localization in hospitals. To locate patients., positions, and doctors, a BLE-enabled device has been utilized to automatically scan the area. Depending on their movement the positional updates are transmitted to the server through Wi-Fi. An efficient, lightweight server-side application has also been developed to efficiently track and manage the data. To determine the coverage across the BLE node, the quantitative coefficient of transmission strength has been utilized. After a thorough investigation at various points, it has been observed that the suggested approach shows 25.9% better accuracy than the other competing scheme which shows the effectiveness of the system. © 2024 IEEE.

关键词： Bluetooth Low Energy (BLE) Indoor navigation system internet of Things (IoT) Received signal Strength Indicator (RSSI) Server Weighted Centroid algorithm Wi-Fi

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2nd NIELIT's international conference on Communication, Electronics and Digital Technologies, NICEDT 2024

2nd NIELIT's International Conference on Communication, Elec...

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2nd NIELIT's international conference on Communication, Electronics and Digital Technologies, NICEDT 2024

ISBN: (纸本)9789819736003

The proceedings contain 79 papers. The special focus in this conference is on Communication, Electronics and Digital Technologies. The topics include: Design and Development of Parallel Beamformer Model for RTL Verification;early Detection of Oral Cancer Using image Processing and Computational Techniques;loRa Enabled IoT Sensor Framework for Monitoring Urban Flood in Guwahati City;study and Implementation of Smart Positioner Prototype for Industrial Applications;tactile internet: A Next Gen IoT technology;a Deep Learning Approach for Hardware Trojan Detection in Netlist of Integrated Circuits with Graph Neural Networks;a Comparative Study of Jpeg and Similar Compression Standards for Wireless Communication;iot-based Transport Monitoring System for Pharmaceutical Industry;non-intrusive Remote Apiculture Monitoring System;design and Analysis of Enhanced Bandwidth Slotted Logarithmic Spiral Patch Antenna for 5G Communication;IoT based Real-Time Automatic Number Plate Detection Using OpenCV;prompt Engineering for the Automated Generation of Weaving Pattern;blood Disease Detection System based on Haemogram Report Using Decision Tree Algorithm;Development of SPR Sensor-based System for Copper Ion Detection in Water;generation of YuBraj Twist and YuBrajTwest Weaves;maintenance and Performance of Solar Water Pump in a Rural Agricultural Community: A Case Study;integrative Analysis of Cancer Gene Expression Using Bio-Inspired Algorithms and Machine Learning: Identification of Key Genes;Potential of AI in Pharma: Bridge the Gap Between Data and Therapeutics;A PC-based Ultrasound Color Doppler Performance Improvement Using Intel® IPPs;Deep Reach Centrality: An Innovative Network Centrality Metric Grounded in Distance and Degree, with Its Performance Analysis Applied to the SARS-CoV-2 Protein–protein Interaction Network.

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Reactive Power Distribution of Mesh Parallel Distributed Generations based on Virtual Impedance 4

Reactive Power Distribution of Mesh Parallel Distributed Gen...

引用

4th international conference on Smart Power and internet Energy systems (SPIES)

作者： Zhang, Xiaobin Li, Yue Wen, Yifan Shen, Jia Li, Chengkai Xiao, Sige Xian Univ Technol Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9781665489577

Compared with the direct parallel distributed generations (DGs), the reactive power distribution of mesh parallel DGs adopted droop control is more complicated. In order to distribute the reactive power between mesh parallel DGs proportionally, the mechanism of reactive power distribution is analyzed, and the virtual impedance including line parameters is introduced in droop control. Considering the effect of virtual impedance on system stability, the small signal model of mesh parallel DGs is established. Finally the value range of the virtual impedance is given based on reactive power proportional distribution, system stability and the rated range of node voltages. Validity of the proposed conclusion is proved by simulation.

关键词： distributed generation mesh parallel structure virtual impedance reactive power distribution

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A Fast Phase-Preserving Imaging Algorithm based on Segmented Pulse Compression for GNSS-InSAR System

A Fast Phase-Preserving Imaging Algorithm based on Segmented...

引用

2022 IEEE international conference on signal Processing, Communications and Computing, ICSPCC 2022

作者： Zhou, Jingtian Liu, Feifeng Wang, Zhanze Xu, Zhixiang Zhang, Shuyao Zeng, Zhangfan Beijing Institute of Technology School of Information and Electronics Beijing100081 China Key Laboratory of Electronic and Information Technology In Satellite Navigation Beijing Institute of Technology Ministry of Education Beijing100081 China Hubei University School of Computer Science and Information Engineering Wuhan China

ISBN: (数字)9781665469722

ISBN: (纸本)9781665469722

In GNSS-based InSAR systems, in order to obtain high azimuth resolution, more than 600s data need to be acquired, which results in large data amount. In this paper, a fast phase-preserving imaging algorithm based on segmented pulse compression is proposed to reduce calculation of GNSS-InSAR system. First, a segment echo signal processing model is established based on bistatic configuration. Then, calculation complex of pulse compression is reduced through data segments along range direction. Finally, pulse compression result for imaging is obtained by summing the segment result and image result is obtained by back projection algorithm. Raw data results suggest the effectiveness of the fast phase-preserving imaging algorithm. © 2022 IEEE.

关键词： image segmentation

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2nd NIELIT's international conference on Communication, Electronics and Digital Technologies, NICEDT 2024

2nd NIELIT's International Conference on Communication, Elec...

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2nd NIELIT's international conference on Communication, Electronics and Digital Technologies, NICEDT 2024

ISBN: (纸本)9789819736034

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image Denoising Using Feature Map based Convolutional Neural Networks

Image Denoising Using Feature Map Based Convolutional Neural...

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2023 IEEE international conference on Recent Trends in Electronics and Communication, ICRTEC 2023

作者： Ravi, A. Dupaguntla, Gnanasree Tadepalli, Devi Krishna Vissamsetti, Swetha Achanta, Radha Krishna Pscmr College of Engineering and Technology Department of Ece Vijayawada India

ISBN: (纸本)9798350396195

Noise corruption is inexorable in image recognition and it may heavily agitate the optical features of the capturing image. Convolutional Neural Networks (CNNs) have acquired good contemplation in the research of denoising. They possess various approaches to removing noise from a degraded image and to reconstruct an image with high visual quality. Because of its stratified learning and self-operating feature extraction capabilities, CNN has become useful for Machine Vision tasks. Furthermore, these methods mostly train a specified model for every noise level and desire multiple methods for denoising images with various noise levels. Large feature sets result in producing a noise effect, which causes an over-fitting of the network. A new method of Feature Map based Convolution Neural Network (FMBCNN) has been introduced for image denoising. The quantitative analysis is performed by calculating four metrics of MSE (Mean Square Error), PSNR (Peak signal to Noise Ratio), SSIM (Structural Similarity Index), and Entropy. They put forward a building block for Convolutional Neural Networks that tends to increase channel interdependencies at nearly no cost of computation. The weights accompanying a kernel also called a mask, are tuned to choose features dynamically. The performance of classification, segmentation, and detection modules is heavily influenced by feature selection. © 2023 IEEE.

关键词： Entropy

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