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检索条件"任意字段=Conference on Algorithms, Devices, and Systems for Optical Information Processing"

共 3200 条记录，以下是161-170 订阅

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Evolution of real-time processing of visual information over four decades: a retrospective as outlook to the future of real-time imaging

Evolution of real-time processing of visual information over...

引用

Real-time processing of Image, Depth and Video information 2023

作者： Carlsohn, Matthias F. Engineering and Consultancy Dr. Carlsohn for Computer Vision and Image Communication Bremen Germany

ISBN: (数字)9781510662636

ISBN: (纸本)9781510662629

The expectations and demands for real-time performance for processing of visual information usually overloaded contemporary computer systems at all times. Increasing hardware performance enabled the use of more complex analysis and vice versa. For a long time, this led to a mutual fertilization of electronics and computer programs or architectures and algorithms with coherent data structures. Appropriate tool sets marked corner stones and boosted some significant developments. However, up to now one got always the impression that the requirements were always heading the possible performance and the open question becoming more serious is: where will it end? This paper provides a short rush through four decades of real-time image processing with a conclusion for an outlook into future opportunities and current developments providing guidelines to host corresponding research results by this conference in the coming years. New concepts, programming paradigms and production technologies are paving the way for future image processing solutions providing real-time capabilities. © 2023 SPIE.

关键词： Parallel architectures

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Research on the processing algorithm for solar cell characterization data 2

Research on the processing algorithm for solar cell characte...

引用

2nd International conference on Electronic information Engineering and Computer Communication, EIECC 2022

作者： Gui, Ruoxia Cheng, Jin Li, Junming Zhang, Chunqian Qin, Lei Research Center for Sensor Technology Beijing Key Laboratory for Sensor School of Applied Sciences Beijing Information Science and Technology University Jianxiangqiao Campus Beijing100101 China Beijing Key Laboratory for Optoelectronic Measurement Technology Beijing Information Science & Technology University Beijing100192 China

ISBN: (纸本)9781510663121

The research of solar cells has gone through three generations, silicon solar cells, thin film solar cells and perovskite solar cells. There are a variety of characterization methods used to analyze the factors that affect the performance of solar cells. Thus far, there are some deficiencies in the research of algorithms of the characterization methods themselves. Three types of data: current density-voltage (J-V) curves, X-ray diffraction (XRD) spectrum and absorption spectrum are the most essential characterization methods. Here, the processing algorithms of these three kinds of characterization data are studied, intend to help researchers to solve the practical problems more efficiently, and improve the accuracy of experimental results. In this paper, the process of processing algorithm are summarized in the way of flow chart, and combined with the example to show in turn. © 2023 SPIE.

关键词： Silicon solar cells

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Design, simulation, and evaluation of a low-cost photometer for dissolved ozone measurement

Design, simulation, and evaluation of a low-cost photometer ...

引用

IEEE International conference on Microwaves, Communications, Antennas, Biomedical Engineering and Electronic systems (COMCAS)

作者： Petani, Lisa Tils, Dominik Wuehrl, Lorenz Sieber, Ingo Pylatiuk, Christian Karlsruhe Inst Technol Inst Automat & Appl Informat Karlsruhe Germany

ISBN: (纸本)9798350348194;9798350348187

The measurement of the dissolved ozone concentration is beneficial in various areas, where ozone is applied, such as medicine, disinfection, food processing, and wastewater treatment. Especially for medical ozone therapy, the measurement directly before and during the treatment is essential to avoid over- and under-dosing. For the wide range application of ozone measurement during medical therapy and in research, low-cost and reproducible measurement devices are indispensable. We present a low-cost photometer that measures the ozone concentration with UV photometry. It consists mainly of 3D-printed parts, while all other parts are commercially available. The root mean squared percentage error of the designed photometer is 14.68% and the root mean squared error is 1.04mg l(-1). We measured concentrations between 0mg l(-1) and 19 mg l(-1), since higher concentrations cannot be produced with the ozone generator used. In principle, however, higher concentrations can also be measured with the photometer, such as the concentrations typical in ozone therapy of up to 30 mgl(-1). We achieve good measurement results with the photometer in comparison with a commercial reference measuring instrument for dissolved ozone, although the reference instrument has a mean square error of 8.2%, but is more expensive by a factor of 17 than the photometer presented here. Low-cost instruments, such as the photometer, provide accurate and inexpensive measurements that are adaptable to a wide range of applications. For example, the photometer can be used in medicine for ozone therapy. The ozone concentration can be measured directly before the injection and thus before the treatment.

关键词： photometer optical sensor dissolved ozone 3D-printer low-cost Raspberry Pi

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Research of Gesture Recognition System Based on OpenCV 7

Research of Gesture Recognition System Based on OpenCV

引用

7th IEEE information Technology, Networking, Electronic and Automation Control conference, ITNEC 2024

作者： Mao, Xiangfang Qiao, Yanhua Li, Jianna Ma, Huijuan School of Information Science and Engineering Tianjin TianShi College Tianjin China

ISBN: (纸本)9798350370782

Currently, the primary modes of human-computer interaction still revolve around traditional devices like mice and keyboards. Technologies such as face recognition, emotion recognition, voice recognition, and gesture recognition have gained increasing attention, making the ways of human-computer interaction more flexible and vivid. This paper mainly focuses on gesture recognition systems in natural scenarios. OpenCV provides various image processing algorithms that can capture image and video information from digital cameras and convert them into binary image information recognized by computers through grayscale image processing. Then, the binary images are filtered and segmented. After extracting the shape of the hand, the contour features of the hand are analyzed. In a normal natural environment captured by a camera, corresponding commands are extracted based on the position and shape of the gestures, enabling simple human-computer interaction. © 2024 IEEE.

关键词： Binary images

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Magnetic Field Sensing with Multi-Material Printed Fiber-Tip Microcantilever 15

Magnetic Field Sensing with Multi-Material Printed Fiber-Tip...

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15th International conference on information Optics and Photonics, CIOP 2024

作者： Huang, Haoqiang Liao, Changrui Zou, Mengqiang Wang, Yiping Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing Key Laboratory of Optoelectronic Devices and Systems Ministry of Education/Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Shenzhen518107 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

Based the advanced "Lab on Fiber" technology and femtosecond (Fs) laser induced two-photon polymerization (TPP) technology, polymer microstructures printed on fiber tip have great potential as high sensitivity micro-sensors. However, additional functionalization is usually required, the traditional treatments such as electron beam sputtering and chemical coating cannot achieve precise functionalization of local microstructure and require additional post-processing. In this work, we report a successive multi-material on-fiber TPP strategy for 4D-microstructure fabrication, and prepare a fiber-tip polymer magnetic microsensor in one step. First, a cantilever is printed on the fiber tip to form a Fabry-Perot (F-P) interferometer. Then, using a self-made magnetic fluid photoresist, a magnetic cube is printed on the cantilever tip as a magnetically responsive element. This method achieves precise functionalization of local microstructure in one step, avoiding further post-processing. The prepared microcantilever magnetic sensor achieves a high sensitivity of 119 pm mT-1, providing an ultra-compact optical solution for high-resolution measurements of weak magnetic fields. With the rapid development of advanced intelligent materials, the multi-material on-fiber TPP strategy can be extended to other stimulus-response materials, offering new guidance for manufacturing various stimulus-response micro-sensors and micro-actuators on fiber tip. © 2024 SPIE.

关键词： Nanocantilevers

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Analyzing Radar Cross Section signatures at automotive microwave radar 3

Analyzing Radar Cross Section signatures at automotive micro...

引用

3rd International Computing Imaging conference, CITA 2023

作者： Wang, Zizheng Qi, Feng Wu, Hongming Xidian University Xi’an710126 China Shenyang Institute of Automation Chinese Academy of Sciences China The Key Laboratory of Liaoning Province in Terahertz Imaging and Sensing Shenyang110169 China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China The Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110169 China College of information science anf engineering Northeastern University Liaoning Province Shenyang110819 China

ISBN: (纸本)9781510671409

With the increasing demand for autonomous vehicles, the reliable detection and recognition of objects have become paramount. Millimeter-wave radar systems operating at frequencies such as 94GHz offer several advantages, including high resolution, precise range measurement, and resilience to adverse weather conditions. However, accurately characterizing the RCS of objects at this frequency range is essential to optimize the performance of these radar systems. In this work, we present Radar Cross Section (RCS) measurements of various objects commonly encountered on the road such as the metal balls, the bricks. The acquired findings illuminate the radar signal fluctuations demonstrated by different entities at a frequency of 94GHz. This knowledge serves as a foundation for developing robust algorithms and signal processing techniques that enhance the object detection, classification, and tracking capabilities of radar-based autonomous driving systems. Moreover, our research provides a valuable dataset of RCS measurements for different objects at 94GHz, which can serve as a benchmark for future studies in the field of radar system design and testing. The availability of such a dataset facilitates the development and validation of radar system models, the evaluation of sensor fusion approaches, and the comparison of performance across different radar hardware and signal processing algorithms. The results contribute to the advancement of radar-based autonomous driving systems by providing crucial insights into the scattering characteristics of objects at millimeter-wave frequencies. The findings have practical implications for optimizing the design, testing, and performance of radar systems, ultimately enhancing the safety and efficiency of autonomous vehicles in real-world scenarios. © 2023 SPIE.

关键词： Millimeter waves

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EM2-YOLO: Lightweight Remote Sensing Image Detection 5th

EM2-YOLO: Lightweight Remote Sensing Image Detection

引用

5th International conference on 3D Imaging Technologies—Multidimensional Signal processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Liu, Xinyi Song, Yaolian Wang, Can School of Information Engineering and Automation Kunming University of Science and Technology Yunnan650500 China

ISBN: (纸本)9789819751808

Remote sensing photographs have a wealth of information, and object detection methods are crucial in this. On mobile and embedded platforms, deep learning-based target identification algorithms are challenging to implement. Additionally, the issues of delayed target detection and poor accuracy of small target detection for remote sensing photos must be resolved immediately. To address these issues, we provide EM2-YOLOv4, a simple method for recognizing remote sensing images. MobileNetv2 acts as the backbone network to reduce model complexity, while depth-separable convolution enhances detection speed. Additionally, we introduce a feature enhancement module and an Efficient Channel Attention (ECA) module to improve model accuracy. To address the issue of unequal assignment of positive and negative samples, we incorporate Focal Loss into the loss function. Experimental demonstrate that the model can perform detection at 45 frames per second with an average accuracy of 94.11%. The model has been significantly reduced, as seen by the fact that it is only 48 MB in size, but it still maintains good detection accuracy and accelerates detection. The model is ideal for usage on embedded devices because of this feature. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： optical remote sensing

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A Hybrid Iris Recognition System Model Based on Presentation Attack Detection and Traffic Monitoring Module on AIoT System 10th

A Hybrid Iris Recognition System Model Based on Presentation...

引用

10th International conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024

作者： Liu, Jishun Shen, Liang Wu, Haixia Lin, Bei Cui, Zhipeng The Third Research Institute of the Ministry of Public Security Shanghai China Shanghai Wudun Information Technology Co. Ltd. Shanghai China

ISBN: (纸本)9789819787456

The integration of AI technology with IoT devices, as in the case of Artificial Intelligence of Things (AIoT), has enabled more efficient and intelligent processing and analysis of data than traditional IoT systems. However, the use of biometric information by AIoT devices can pose new security risks, such as presentation attacks and privacy breaches, particularly for immutable features such as iris information, which can lead to long-term security vulnerabilities when compromised. Most existing iris recognition system security models are currently designed to address only direct presentation attack algorithms. Therefore, such models cannot address other security threats. To address these challenges, this study proposes a hybrid iris recognition system security protection model that employs presentation attack detection, flow monitoring, and black list restrictions to enhance the overall security of AIoT devices and improve the efficiency of protection. Specifically, the model aims to prevent presentation attacks and flow attacks against the iris recognition system, which may compromise the security of biometric information. The proposed method is expected to increase AIoT devices security against potential threats to sensitive information. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Data privacy

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Diagnostics of Technological Machines of Grain processing Enterprises 10th

Diagnostics of Technological Machines of Grain Processing En...

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10th International conference on Industrial Engineering, ICIE 2024

作者： Kalandarov, P.I. Sharifov, H.S. Khayitov, A.N. Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University 39 Kari Niyazov Street Tashkent100000 Uzbekistan Bukhara Institute of Natural Resources Management of the National Research University of Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 32 Highway Gazli Bukhara200100 Uzbekistan

ISBN: (纸本)9783031658693

As a result of the conducted research, the scientific and practical foundations of creating distributed systems for automatic monitoring and diagnostics of the technical condition of grain processing equipment using diagnostic information analysis methods are discussed. The article provides comprehensive information about methods and devices for detecting excess vibration in machine mechanisms used in production processes. Due to the continuous movement of the transmissions of the electrical parts of production and processing equipment, there is loosening of the fasteners and wear of the mechanism, which in turn causes excessive vibration. The article covers the issues of general diagnostics of the operation mode and control parameters of the excessive vibration detection mechanisms using modern measuring devices and controllers, as well as creation of control feature. Reliability research is based on systematic acquisition of knowledge, practical application of knowledge and their assimilation, a system of knowledge and skills is presented, built according to a block diagram, aimed at ensuring the reliability of both technological research and industrial equipment, ensuring a high level of reliability and durability of equipment and machines, algorithms for planning and implementing the development of technical and organizational The reliability management system is demonstrated using computer modeling methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Reliability

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An efficient and robust corner detection algorithm for furniture boards

An efficient and robust corner detection algorithm for furni...

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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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