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Smart Electronics and Communication Systems (ISENSE), International Conference on

作者： Arun T Nair Nanditha N Varma Nandakumar R National Institute of Electronics and Information Technology Calicut

ISBN: (数字)9798331528126

ISBN: (纸本)9798331528133

This work offers a thorough method for real-time dehazing of drone-captured images by different filtering techniques with post-processing improvements. Enhancing visibility and picture clarity in hazy situations is the main goal since it is essential for applications like environmental monitoring, navigation, and surveillance. In order to estimate the atmospheric light and transmission map, the suggested methodology makes use of the dark channel. A farrow filter and a guided filter are then applied to improve the transmission. Metrics including the PSNR, SSIM, Execution time, and MSE that are derived from Python-based image processing implementations are used to assess the effectiveness of the dehazing algorithms. The outcomes show notable gains in processing efficiency and image clarity. In order to accelerate the performance, this method was implemented on an FPGA based SoC. Power consumption and throughput of the FPGA - based solution were evaluated, demonstrating its effectiveness and appropriateness for real-time applications.

关键词： Surveillance Video sequences Random access memory Gray-scale filtering algorithms Throughput Real-time systems System-on-chip Field programmable gate arrays Tuning

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A GPS Receiver Adaptive Digital Beamforming Interference Suppression Algorithm Based on Kalman Filter

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Chinese Journal of Electronics 2023年第2期22卷 433-436页

作者： Wenrui Ding Yunlong Zhu Bo Zhang Dongkai Yang Institute of Unmanned Air Vehicle Beihang University Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China School of Electronic and Information Engineering Beihang University Beijing China

This paper proposed a novel Global positioning system (GPS) receiver adaptive Digital beamforming (DBF) interference suppression algorithm, which remodeled Minimum power distortionless response (MPDR) beamforming by transforming it into Minimum mean square error (MMSE) beamforming in the frame of Generalized sidelobe canceller (GSC), and introduced Kalman filter (KF) to carry out adaptive beamforming. Theory analyses and simulation results indicate that this algorithm has higher output Signal to interference and noise ratio (SINR) than Recursive least square (RLS) and Least mean square (LMS) adaptive beamforming algorithms which are in common use, and similar convergence rate with RLS algorithm.

关键词： Interference suppression Adaptive systems Array signal processing Simulation Receivers Transforms filtering algorithms

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Fall Detection System Based on YOLO Algorithm and MobileNetV2 Model

Fall Detection System Based on YOLO Algorithm and MobileNetV...

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International Conference on Systems and Informatics (ICSAI)

作者： Chunxiao Han Jingyan Zhang Han Wu Tianjin Key Laboratory of Information Sensing & Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (数字)9798331510138

ISBN: (纸本)9798331510145

Accidental falls are the major causes of injury among elderly people living alone. However, traditional fall detection algorithms usually have missed or false detections problems. In this paper, we design a fall detection system based on YOLO algorithm and MobileNetV2 model. First, detection frame coordinates and joint coordinates of the human body are fused as feature information, and background information is filtered out. A lightweight deep learning model, MobileNetV2, is then used for classification. Compared with commonly used lightweight classification models such as ShuffleNet and EfficientNet, the MobileNetV2 model performs better in recognizing fall behavior. Our system can effectively distinguish fall behavior from daily activities, meeting the requirements for fall detection.

关键词： YOLO Deep learning filtering algorithms Information filters Feature extraction Classification algorithms Fall detection Older adults Informatics Injuries

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Hardware Implementation of an a-Trimmed Adaptive Median Mean Filter

Hardware Implementation of an a-Trimmed Adaptive Median Mean...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Nathan Clarks Matthew Schweinfuss Enass Hriba Firas Hassan Electrical & Computer Engineering and Computer Science (ECCS) Department Ohio Northern University OH USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

In this paper, we provide and describe a hardware implementation of an $\alpha$ -trimmed adaptive median mean filter capable of restoring images affected by both Gaussian and impulse noise without causing blurriness in the reconstructed image. The algorithm was implemented on an FPGA device and achieved real-time processing capabilities of 50 frames/second for a frame of 1024x768 pixels while utilizing 3363 LUTs, 392 FFs, and 1 DSP block.

关键词： Image edge detection Noise Adaptive filters filtering algorithms Hardware Real-time systems Image restoration

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A Machine Learning-based Change Detection Scheme for the Remote Sensing Images using Gaussian and Lee filters

A Machine Learning-based Change Detection Scheme for the Rem...

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International Conference on Devices, Circuits and Systems (ICDCS)

作者： Bhavana.N. Sivadas Jeshma Ullas Sourabh Paul School of Computer Science and Engineering (SCOPE) Vellore Institute of Technology (VIT) Chennai Tamil Nadu India School of Electronics Engineering (SENSE) Vellore Institute of Technology (VIT) Chennai Tamil Nadu India

ISBN: (数字)9798350350470

ISBN: (纸本)9798350350487

This article presents an updated change detection algorithm specifically for remote sensing synthetic aperture radar (SAR) images and optical images. This method uses Lee and Gaussian filtering techniques to overcome challenges such as speckle noise and illumination changes in SAR images. First, apply the Lee filter to the SAR image and use the Gaussian filter to the optical image to remove noise from the image. The Support Vector Machine (SVM) algorithm is then used to identify changes in the two images. Compared with existing methods, the proposed method can provide better PCC values and lower total error (PTE) values. Experiments on different SAR and optical images have confirmed the effectiveness of this method.

关键词： Optical filters Support vector machines Integrated optics filtering filtering algorithms Optical imaging Adaptive optics

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Object Tracking in Surveillance System using Gaussian-Sum Filter And ACF Detection

Object Tracking in Surveillance System using Gaussian-Sum Fi...

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Student Conference on Research and Development (SCOReD)

作者： Christanto Febrian Wibisono Hilal Huda Muhamad Irsan Aji Gautama Putrada Syifak Binti Izhar Hisham School of Computing Telkom University Bandung Indonesia School of Computing CAATIS Tel-U Bandung Indonesia School of Computing Telkom University Jakarta Jakarta Indonesia Science Computer Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

This paper presents a study on object tracking in surveillance systems using Gaussian-Sum Filter and Aggregate Channel Features (ACF) detection to address the challenges of accurately tracking multiple objects in dynamic environments. Object tracking is crucial in computer vision, with applications from surveillance and security to autonomous navigation and robotics. This study employs the Gaussian-Sum Filter, a proven Bayesian filtering algorithm known for its predominance in non-linear scenarios, which keeps object tracking more consistent over time. However, since the ACF detection method can detect objects over multiple frames with higher accuracy than our initial detections, we combine it with initial ones. Performance testing is conducted across four datasets, using key metrics such as precision, Multiple Object Tracking Precision (MOTP), and Multiple Object Tracking Accuracy (MOTA) to evaluate effectiveness. The results show that while Gaussian-um Filter combined with ACF detection achieves different precision with specific datasets (7%-98%) and MOTP rates (10 %-73 %), challenges arise in maintaining uninterrupted tracking accuracy, as evidenced by very low MOTA (-6%-10%) and a significant rate of false negatives, especially in complex scenarios with occlusions. These findings suggest that although Gaussian-Sum Filter and ACF detection are effective for initial detection and data handling, enhancements or hybrid methods may be required for applications demanding high accuracy in continuous multi-object tracking.

关键词： Matched filters Accuracy Surveillance Data handling Object detection filtering algorithms Feature extraction Bayes methods Object tracking Testing

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Fast Bidirectional A-Star Algorithm Based on Radar Image Data Fusion for Polar Ship Route Planning

Fast Bidirectional A-Star Algorithm Based on Radar Image Dat...

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International Conference on Computers, Communications, and Systems (ICCCS)

作者： Huafeng Wu Chenyang Jiao Xiaojun Mei Bing Han Zhongdai Wu Yuxuan Zhang Shanghai Maritime University Shanghai China Shanghai Ship and Shipping Research Institute Co. Ltd. Shanghai China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

Path planning is a significant issue in the current research on ice navigation. Most existing studies utilize sea ice models or ice charts for large-scale polar ship route planning. However, the dynamic trends in weather and ice conditions in polar waters make it challenging for existing research to meet the needs of small-scale, flexible route planning and to accurately and effectively avoid the risk of ice collision. To address this, the study reconstructs the sea ice navigation scene using marine radar imaging technology and applies an optimized bidirectional A-star algorithm to design a polar ice surface ship navigation route planning scheme. The improved bidirectional A-star algorithm takes into account both distance and turning angle, introduces an offset $p$ to prioritize nodes closer to the destination. Additionally, in this research, the $Z$ (x,y) function is applied to filter nodes within the closed list, discarding those that fail to satisfy the criteria to prevent irregular paths. To enhance the ship's turning path smoothness, cubic Bezier curves are employed as a replacement for polyline turning paths. Overall, the results of the simulation experiments confirm the effectiveness of the improved bidirectional A-star algorithm in path planning.

关键词： Navigation Radar Radar imaging filtering algorithms Turning Ice Path planning

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Performance of spatial digital image filtering on a real Advanced Driver Assistance System platform

Performance of spatial digital image filtering on a real Adv...

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Zooming Innovation in Consumer Electronics International Conference (ZINC)

作者： Kristina Opač ak Marijan Herceg Jelena Kovač ević Iš tvan Papp TTTech Auto CEE Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia RT-RK Institute for Computer Based Systems Novi Sad Serbia Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

ISBN: (数字)9781665483742

ISBN: (纸本)9781665483759

In this paper, the implementation and optimization of different spatial filters on the realistic Advanced Driver Assistance Systems (ADAS) platform is performed. In particular, the moving average, high-pass, median and Gaussian spatial filters are implemented on the ADAS Alpha board. The optimization of the implemented filters is performed in the software and hardware domain on different Alpha board processors to improve the filter's execution times. After optimization, the performance of the implemented filters is measured and compared with the implementation on the personal computer. The given results show comparable execution times of the optimized solution.

关键词： Technological innovation Program processors Software algorithms filtering algorithms Spatial filters Software Hardware

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Two-Step Algorithm for Matched filtering of Signals

Two-Step Algorithm for Matched Filtering of Signals

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Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO)

作者： A. N. Degtyaryov A. S. Kozhemyakin I. L. Afonin G. V. Slyozkin A. L. Polyakov Sevastopol State University Sevastopol Russia

ISBN: (数字)9781665470643

ISBN: (纸本)9781665470650

To lower the impact of non-linear distortions on the accuracy of reception of information under multipath signal transmission conditions and additive noise it is proposed to use a two-step signal processing. The first step includes minimization of dispersion of the noise caused by symbol-to-symbol interference and non-linear distortions of a signal. This dispersion is minimized by determining the orthogonality weight of the basis functions that make up the signal. The second step includes application of a classic matched filter.

关键词： Additive noise Matched filters Nonlinear distortion Signal processing algorithms Nonlinear filters filtering algorithms Minimization

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IVCM Image Enhancement Based on Improved Guided Filter

IVCM Image Enhancement Based on Improved Guided Filter

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Algorithm, Image Processing and Machine Vision (AIPMV), International Conference on

作者： Wen Qiao Fang Wang Hua Yu Jiying Gao Taiyuan University of Technology Machine Vision Taiyuan Shanxi Province China Department of Cornea Shanxi Eye Hospital Taiyuan Shanxi Province China

ISBN: (数字)9798350390254

ISBN: (纸本)9798350390261

In order to improve the low-quality of manually captured IVCM(In Vivo Confocal Microscopy, IVCM)images, this paper proposes an IVCM image matching algorithm with guided filter enhancement based on meanshift clustering. Firstly, the original IVCM image is clustered and segmented using the meanshift algorithm, and the segmented image is used as the guiding image to realize the guided filter enhancement of the image; secondly, the key points of the neural texture of the IVCM image are extracted by the SIFT(scale-invariant feature transform)algorithm; finally, the two-step matching method is used to realize the matching of the two IVCM images. After experiments, it is proved that the proposed algorithm in this paper can extract the key information of the neural texture in the IVCM image more effectively and improve the accuracy of image alignment.

关键词： Matched filters Image segmentation Accuracy Image matching Clustering algorithms Object segmentation filtering algorithms Feature extraction Information filters Image enhancement

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