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2024 International Conference on Image, Signal processing, and Pattern Recognition, ISPP 2024

作者： Chen, Long Jiang, Junfeng Tang, Hengliang Xie, Xiaohua Chen, Xiang Liu, Jing College of Electronics and Information Engineering Shenzhen University Shenzhen China Sun Yat-sen University Guangzhou China Shenzhen China Xinguang Intelligent Systems Co. Ltd in Guangdong Zhongshan China

ISBN: (纸本)9781510680425

In the intelligent inspection of furniture boards, wood debris generated during manufacturing can interfere with the imaging process. This leads to burr disturbances at the corners of the boards. Existing corner detection methods exhibit lower detection accuracy under the interference of these disturbances. To overcome this issue, this paper presents a corner detection algorithm tailored for furniture boards that incorporates the Random Sample Consensus (RANSAC) algorithm and line fitting techniques based on the Huber loss function. To enhance detection efficiency, our algorithm initially identifies horizontal and vertical edges near a corner. This preliminary step facilitates subsequent corner detection. This study introduces a test dataset for evaluating the accuracy and efficiency of algorithms. A battery of comparative experiments, including benchmarks with conventional methods, were conducted. The results demonstrate that our algorithm significantly enhances the efficiency and robustness of corner detection under a variety of complex burr interference conditions. © 2024 SPIE.

关键词： Furniture manufacture

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Indoor Human Fall Detection Algorithm Based on Wireless Sensing

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Tsinghua Science and Technology 2022年第6期27卷 1002-1015页

作者： Chao Wang Lin Tang Meng Zhou Yinfan Ding Xueyong Zhuang Jie Wu Key laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai UniversityShanghai 200444China Department of Computer and Information Sciences Temple UniversityPhiladelphiaPA 19122-6096USA

As the main health threat to the elderly living alone and performing indoor activities,falls have attracted great attention from institutions and ***,fall detection systems are mainly based on wear sensors,environmental sensors,and computer vision,which need to be worn or require complex equipment ***,they have limitations and will interfere with the daily life of the *** the basis of the indoor propagation theory of wireless signals,this paper proposes a conceptual verification module using Wi-Fi signals to identify human fall *** module can detect falls without invading privacy and affecting human comfort and has the advantages of noninvasive,robustness,universality,and low *** module combines digital signal processing technology and machine learning *** paper analyzes and processes the channel state information(CSI)data of wireless signals,and the local outlier factor algorithm is used to find the abnormal CSI *** support vector machine and extreme gradient boosting algorithms are used for classification,recognition,and comparative *** results show that the average accuracy of fall detection based on wireless sensing is more than 90%.This work has important social significance in ensuring the safety of the elderly.

关键词： wireless signal channel status information fall detection wireless sensing

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Convolutional Neural Network Model to Improve Image processing on A C-arm Imaging

Convolutional Neural Network Model to Improve Image Processi...

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2024 International Conference on Remote Sensing, Mapping, and Image processing, RSMIP 2024

作者： Huang, Jindai Zhang, Jingli Zhang, Dianchen People's Liberation Army 252 Hospital Baoding China

ISBN: (纸本)9781510680012

In the field of medical imaging, C-arm systems play a pivotal role in surgeries, especially interventional surgeries. However, the current C-arm imaging system cannot adapt to the application scenarios due to algorithm limitations. Therefore, in order to improve the quality of diagnostic and therapeutic interventions, it is necessary to improve the quality of C-arm imaging and to fulfill the various requirements of different scenarios by improving the image processing techniques associated with C-arm imaging. This article explores how to improve C-arm image processing using convolutional neural network (CNN)-related algorithms. CNNs are known for their ability to extract complex features from images, which can be used for contrast enhancement, noise reduction, artifact removal, and resolution enhancement. Through a comprehensive review of state-of-the-art applications and technologies, this study proposes an innovative method of applying CNN for image processing in C-arm systems, improving image quality and thus providing potential advancements in clinical diagnosis and surgery. In terms of real-time image enhancement, integrating CNN into the C-arm imaging pipeline has demonstrated promising results, providing a reference for medical imaging learning and research. This article discusses the methods, experimental results, and implications of incorporating CNN into C-arm imaging, emphasizing that this technology can greatly improve image quality and indicating the potential of artificial intelligence technology in C-arm imaging applications. © 2024 SPIE.

关键词： Medical imaging

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optical Character Recognition for Urdu Text: A Review of Techniques, Challenges, and Future Directions 5

Optical Character Recognition for Urdu Text: A Review of Tec...

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5th IEEE International Conference on Advances in Electronics, Computers and Communications, ICAECC 2023

作者： Shaik, Moinuddin Ahmed Abdul, Wahid Maulana Azad National Urdu University Dept. of Computer Science and Information Technology Hyderabad India

ISBN: (纸本)9798350305449

In recent years, Urdu optical Character Recognition (OCR) systems have received considerable attention due to the increasing demand for automated recognition and analysis of text, which requires the development of robust OCR systems to convert printed and handwritten Urdu text into digital format. This article aims to provide a comprehensive overview of the most recent advances in OCR systems for Urdu. Analysing and synthesising 30 relevant research articles published between 2018 and 2023 to determine their contributions and future directions. Numerous studies have explored the use of deep neural networks, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs), to achieve high accuracy in character recognition by incorporating evolutionary algorithms, transfer learning, augmentation, and holistic unconstrained recognition systems. These models have demonstrated promising offline and online Urdu handwriting recognition results. The reviewed articles also shed light on the difficulties and limitations of existing Urdu OCR systems, such as the lack of standardised datasets, the dearth of annotated training data, and the need for robustness against noise and variations in handwriting styles. The literature discusses the development of more efficient algorithms, the investigation of multi-domain approaches, and the integration of deep learning techniques with other image processing techniques as future directions. The findings of this review will help researchers and practitioners in understanding the most recent techniques and challenges in Urdu OCR systems. © 2023 IEEE.

关键词： optical character recognition

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Hole repair of 3D terrain mesh in satellite stereo image reconstruction

Hole repair of 3D terrain mesh in satellite stereo image rec...

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2024 International Conference on Remote Sensing, Mapping, and Geographic information systems, RSMG 2024

作者： Bao, Qiwei Liu, Jun Liu, Xining Zhao, Limin Yuan, Zhanliang Chen, Xingfeng Li, Jiaguo Li, Huafu Zhang, Haixiang School of Surveying and Land Information Engineering Henan Polytechnic University Jiaozuo454003 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Sanya Institute of South China Sea Geology Guangzhou Marine Geological Survey China Geological Survey Sanya572024 China

ISBN: (纸本)9781510685826

When constructing a 3D surface grid using point cloud data closely matched with high-resolution satellite stereo images, holes often appear due to matching failures or limitations of triangulation algorithms, affecting the grid's integrity and the accuracy of subsequent applications. To solve this problem, a boundary contraction algorithm is studied for repairing mesh holes. The research focuses on different terrain conditions such as mountains, plains, and cities, and evaluates the effectiveness of boundary contraction algorithms in repairing holes. Using visual inspection methods, the quality of the repaired mesh is checked to ensure its integrity, smoothness, continuity, and topological correctness. The experimental results of GF-7 satellite images show that the boundary contraction algorithm can effectively fill holes in various terrain environments, significantly improving the geometric quality and overall integrity of the mesh, verifying its feasibility as a reliable mesh repair method, and providing strong support and verification for the application of the boundary contraction algorithm in actual terrain data processing. © 2024 SPIE.

关键词： Mesh generation

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Adaptive analysis of rapid prediction of coal quality information based on image analysis

Adaptive analysis of rapid prediction of coal quality inform...

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2022 International Conference on Computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2022

作者： Liu, Ming Zhang, Hua CHN Energy Xinjiang Chemical Co. Ltd. Xinjiang Urumqi831404 China

ISBN: (纸本)9781510663350

Machine vision technology has shown great potential for development and application in the coal heat utilization and coal chemical production process It is important to carry out image analysis-based stability adaptation analysis of coal heat utilization and coal chemical equipment. To further expand its application, this work reviewed the characteristics of different vision sensor systems and image processing algorithms in the process of image acquisition and processing, conducted applicability analysis for rapid prediction of coal quality, presented the current problems and future development trends of image analysis technology in the coal heat utilization and coal chemical production process. It provided theoretical guidance and reference for promoting automation, intelligence, and mechanization in the coal industry. © 2023 SPIE.

关键词： Forecasting

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optical differentiation based on weak measurements

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OPTICS LETTERS 2022年第15期47卷 3880-3883页

作者： Wang, An Zhu, Junfan Luo, Lan Liu, Xiong Ye, Ling Zhang, Zhiyou Du, Jinglei Sichuan Univ Coll Phys Chengdu 610064 Peoples R China Chinese Acad Sci Key Lab Sci & Technol Space Optoelect Precis Meas Chengdu 610209 Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Peoples R China

optical differentiation shows much potential to be applied in computation due to its strong parallelizability. Currently, each optical differential method can only obtain partial differential information. Here, we propose a general approach to obtain complete differentiation. Compared to previous methods, we can separately obtain the differentiation of amplitude and phase, reserve the negative value of the differentiation, and acquire the differentiation in arbitrary directions of the two-dimensional field. We measure the differentiation of the Gaussian beam to demonstrate this method. A practical experiment of identifying the move direction of the motion-blurred image is also presented to verify the practicability of our method. Our method can further be applied to intelligence algorithms, image identification, and optical analog computing. (C) 2022 Optica Publishing Group

关键词： Gaussian beams Image processing Light beams Light fields optical systems Polarized light

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Error-mitigated photonic variational quantum eigensolver using a single-photon ququart

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OPTICA 2022年第1期9卷 88-95页

作者： Lee, Donghwa Lee, Jinil Hong, Seongjin Lim, Hyang-Tag Cho, Young-Wook Han, Sang-Wook Shin, Hyundong Rehman, Junaid Ur Kim, Yong-Su Korea Inst Sci & Technol KIST Ctr Quantum Informat Seoul 02792 South Korea Korea Univ Sci & Technol KIST Sch Div Nano & Informat Technol Seoul 02792 South Korea Yonsei Univ Dept Phys Seoul 03722 South Korea Kyung Hee Univ Dept Elect & Informat Convergence Engn Yongin 17104 South Korea

Variational quantum algorithms, a representative class of modern quantum algorithms, provide practical uses of near-term quantum processors. The size of the problem that can be encoded and solved on a quantum processor is limited by the dimension of the Hilbert space associated with the processor. One common approach for increasing the system dimension is to utilize a larger number of quantum systems. Here, we adopt an alternative approach to utilize multiple degrees of freedom of individual quantum systems to experimentally resource-efficiently increase the Hilbert space. We report experimental implementation of the variational quantum eigensolver (VQE) using four-dimensional photonic quantum states of single photons. The four-dimensional quantum states are implemented by utilizing polarization and path degrees of freedom of a single photon. Our photonic VQE is equipped with a quantum error mitigation protocol that efficiently reduces the effects of Pauli noise in the quantum processing unit. We apply our photonic VQE to estimate the ground state energy of the He - H+ cation. Simulation and experimental results demonstrate that our experimental resource-efficient photonic VQE can accurately estimate the bond dissociation curve, even in the presence of large noise in the quantum processing unit. We also discuss further possible resource-efficient enhancement of the Hilbert space in photonic quantum processors. Our results propose that photonic systems utilizing multiple degrees of freedom can provide a resource-efficient avenue to implement practical near-term quantum processors. (C) 2022 optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： optical elements Photons Polarization Quantum information processing Quantum noise Wave plates

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Borehole Inner Surface visualization System with vibration Cancellation and Trajectory Smoothing Based on optical Monocular video Camera 9

Borehole Inner Surface Visualization System with Vibration C...

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9th International Conference on Geographical information systems Theory, Applications and Management, GISTAM 2023

作者： Zong, Nan Al-Nuaimy, Waleed Lakany, Heba Worthington, Paul School of Electrical Engineering Electronics and Computer Science University of Liverpool Brownlow Hill Liverpool United Kingdom Department of Engineering & Development Robertson Geologging Ltd. York Road Deganwy United Kingdom

ISBN: (纸本)9789897586491

The rapid digitization and modelling of the planet brings with it increased demand for the tools necessary to process and visualize disparate streams of multivariate and often highly complex geophysical data streams. The rationalization of detection hardware and the integration of sensors offers the potential to economically visually explore and map geophysical environments such as the interior of subterranean boreholes. This paper addresses the challenge of visual reconstruction of the geometry of the inner surface of a borehole from video data collected via a monocular optical camera. We introduce a novel system of algorithms to unwrap the cylindrical borehole inner surface data and to compensate for the offsets and errors arising during data acquisition. Three modules are designed for this task: Unwrapping module consisting o algorithms to generate visualization results of borehole inner surfaces;vibration cancellation module that compensates for rotation and drift errors caused by the movement of detectors, balancing computational cost and performance;Trajectory smoothing based on image convolution signal processing methods to filter out anomalies and interruptions that arise as a result of the other processing stages. The proposed system integrates these modules to generate planar side-view images with a high level of spatial accuracy. This system also contributes to establish a novel and easy-to-access visualization tool of boreholes with simplified detectors that only consists of a monocular camera and a fixed circular LED band. Results has demonstrated the system is capable of resisting high frequency drift and the effects of rotation and vibrations in harsh subterranean environments. This novel combination of video and image processing marks a significant improvement over currently available or published borehole video exploration techniques, and can be further extended and enhanced to deliver more accurate multi-sensor 3D modeling and reconstruction of the

关键词： Data visualization

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An Intrusion Detection Method Combining Bayesian Optimization and LightGBM

An Intrusion Detection Method Combining Bayesian Optimizatio...

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2023 International Conference on algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2023

作者： Xu, Dongyuan Hua, Bin School of Information Engineering Ningxia University Yinchuan China

ISBN: (纸本)9781510671881

Network is a double-edged sword, which brings great convenience and some risks at the same time. Then intrusion detection, as a proactive and defensive technical means, plays a very important role in protecting information systems. Traditional intrusion detection systems have the problems of low detection accuracy and poor real-time performance, while the existing network intrusion detection data is not balanced, so this paper proposes an adaptive synthesis algorithm (ADASYN) oversampling + class balancing data balancing algorithm and an intrusion detection method of LightGBM combined with Bayesian optimization algorithm, aiming to solve the above problems. First, data preprocessing we encode the data with labels as well as unique heat encoding to better pass into the model for processing, after that we increase a few classes of data by ADASYN oversampling to make the number of samples in each class relatively balanced, and finally the features are passed into LightGBM for learning and training, and finally validated in the NSL-KDD dataset for multi-class classification experiments, and the results show that Compared with other traditional algorithms, all data are improved and show better performance. © 2023 SPIE. All rights reserved.

关键词： Intrusion detection

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