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检索条件"任意字段=Conference on Optical and Digital Image Processing"

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Three-dimensional digital intelligent patrol inspection system for substation based on digital twin technology 3

Three-dimensional digital intelligent patrol inspection syst...

引用

3rd International conference on image processing and Intelligent Control, IPIC 2023

作者： Liu, Guobing Chen, Zhenliang Xiao, Limin Li, Yixiang Dongguan Power Supply Bureau Guangdong Power Grid Company Guangdong Dongguan523000 China

ISBN: (纸本)9781510668140

Design a three-dimensional digital intelligent patrol system for substation based on digital twin technology, and intelligently patrol the substation equipment to effectively excavate the potential safety hazards of the substation. The physical entity layer uses cameras and sensors to collect the image of substation equipment, parameter data and environmental information, and carries out effective preprocessing of the acquired data;The digital twin virtual model layer calls the relevant data of the physical entity layer, and uses SolidWorks, 3D MAX and Unity3D software to build the digital twin virtual model of the substation;The application layer plans the patrol path and identifies the electronic tag of the equipment according to the substation data sent by the network transmission layer. On this basis, the patrol module applies the Super SAB neural network equipment state perception and prediction method to effectively perceive and predict the status of the substation equipment, and visualizes the patrol results on the human-computer interaction layer. The experimental results show that the system can effectively inspect the substation equipment, present the inspection results through virtual vision, intelligently inspect the substation equipment, and apply it to practical work, which can achieve better intelligent inspection results in the substation. © 2023 SPIE.

关键词： Inspection

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Research and Optimization of Frequency Measurement Algorithms Based on Monobit Receiver 8

Research and Optimization of Frequency Measurement Algorithm...

引用

8th International conference on Communication, image and Signal processing, CCISP 2023

作者： Yu, Haoxiang Wang, Jia Dai, Chen Chu, Ran Gu, Peng School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China Xi'an Institute of Space Radio Technology China Academy of Space Technology Xi'an China

ISBN: (纸本)9798350305838

In the design of conventional single-bit receivers, a high error rate is often observed due to interpolation direction errors near the quantized frequency points caused by the Rife algorithm. To address this issue, this study proposes an optimization technique using a mean filter. By integrating this technique with single-bit quantization and approximate kernel fast Fourier transform (FFT), a 38.4Gbps ultra-wideband single-bit digital receiver based on a single-bit analog-to-digital converter (ADC) and field-programmable gate array (FPGA) is designed. Subsequent MATLAB simulation and FPGA validation demonstrate that this receiver can reduce the frequency measurement error to within 3MHz, meeting the real-time or near real-time frequency measurement requirements for electronic warfare applications. © 2023 IEEE.

关键词： Fast Fourier transforms

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Research on Low-Light image Enhancement method based on UNet 5

Research on Low-Light Image Enhancement method based on UNet

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5th International conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Zhu, Fuyu Fei, Rong Ji, Chengjie School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shannxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China

ISBN: (纸本)9781510691667

As technology develops continuously, digital images are being applied more and more extensively in daily life. digital images are mainly divided into two categories: one is the images obtained by photosensitive devices such as cameras, and the other is the images generated by software. Nevertheless, in low - light conditions, the images captured by traditional photosensitive devices typically suffer from issues like low luminance and subpar visual qualities. These problems pose significant challenges to subsequent image processing and practical applications. Thus, the technology of enhancing low - light images has emerged as a crucial research area for the purpose of elevating image quality. This paper puts forward a solution centered around the improved UNet network to address the issue of image enhancement in low - light settings. The UNet network effectively performs image enhancement through feature extraction, feature fusion, and restoration operations. However, the classical UNet can only process single - channel grayscale images, and the loss function it uses has relatively limited effects in low - light image processing. Therefore, this paper adjusts the number of channels of the UNet network so that it can process three - channel RGB images and improves the loss function. We compared the enhancement effects of L1 Loss, VGG Loss, and SmoothL1 Loss respectively, and carried out a quantitative analysis through evaluation metrics such as PSNR and SSIM. Ultimately, through the combination of the three loss functions and their weighted optimization, the enhancement effect of low - light images is notably enhanced. The innovation of this paper lies in expanding the structure of the UNet network to make it adaptable to three - channel image processing, and improving the quality of image enhancement by improving the loss function. This approach is capable of efficiently enhancing the visual impact of low - light images, thereby offering a practical solution for imag

关键词： Photointerpretation

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GPGPU-based High Throughput image Pre-processing Towards Large-Scale optical Character Recognition 19

GPGPU-based High Throughput Image Pre-processing Towards Lar...

引用

19th IEEE/ACS International conference on Computer Systems and Applications (AICCSA)

作者： Gener, Serhan Dattilo, Parker Gajaria, Dhruv Fusco, Alexander Akoglu, Ali Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA

ISBN: (纸本)9798350310085

Studies have shown that pre-processing digital images through scaling, rotation and blurring type of operations allow optical character recognition (OCR) to focus on the key features in the image and result in improving recognition accuracy. We leverage the open-source Tesseract OCR and show that its accuracy can be improved through a pre-processing flow that includes thresholding, rotation, rescaling, erosion, dilation, and noise removal steps based on a dataset that is formed of 560 phone screen images. However, the serial CPU-based implementation of this flow introduces a latency of 48.32 ms per image on average. Even though time scale is low in the context of a single image, this latency poses as a barrier when processing millions of images with OCR. To address this, we parallelize the entire pre-processing flow on the Nvidia P100 GPU, implement a streaming based execution, and reduce the latency to 0.846 ms. This streaming-enabled implementation enables setting up a GPU based OCR engine to process large scale workloads.

关键词： optical Character Recognition (OCR) Tesseract Leptonica image processing CUDA GPU

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Channel-Equalized Terahertz Compressed Sensing Imaging 49

Channel-Equalized Terahertz Compressed Sensing Imaging

引用

49th International conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)

作者： Kao, Chun-Yu Chiu, Li-Hsuan Mai, Chia-Ming Stantchev, Rayko Ivanov Huang, Yuan-Hao Yang, Shang-Hua Natl Tsing Hua Univ Inst Elect Engn Hsinchu Taiwan Natl Tsing Hua Univ Dept Elect Engn Hsinchu Taiwan Natl Sun Yat Sen Univ Dept Phys Kaohsiung Taiwan

ISBN: (纸本)9798350370331;9798350370324

Among all terahertz (THz) imaging techniques, compressed sensing imaging shows the potential to perform large area detection with faster acquisition time and capability to be integrated with single pixel THz receiver. However, despite the mentioned advantages, unevenly distributed THz beam and spatial modulated optical pump begin to affect the image system and reduce the reconstruction quality within the utilization of larger field of view. Hence, we establish a THz compressed sensing imaging system with equalization procedure along orthogonal basis pursuit (OMP) algorithm to mitigate these effects. Results from imaging experiments demonstrate the effectiveness of the proposed equalization method in improving image reconstruction, presenting a precise mathematical model simulating and non-ideal phenomenon calibration.

关键词： terahertz time-domain spectroscopy compressed sensing imaging channel equalization digital signal processing

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Research on face feature extraction algorithm based on OpenCV with optical enhancements 5

Research on face feature extraction algorithm based on OpenC...

引用

5th International conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Zhang, Li Chen, Shuxi Yu, Anyue Liu, Yuxiang School of Yonyou Digital and Intelligence Nantong Institute of Technology Nantong China

ISBN: (纸本)9781510691667

In the current digital era, face recognition technology is of great significance. Its core lies in the extraction of facial key-point features, which provides a crucial data foundation for subsequent applications. This research focuses on the face feature extraction algorithm based on OpenCV and conducts an in - depth exploration of the relevant functional algorithms and implementation methods. In terms of algorithms, the principle of the AdaBoost algorithm and the working mechanism of the cascade classifier based on Haar - like features are elaborated in detail. The functional implementation covers aspects such as dataset collection and annotation, data pre-processing (including image grayscale processing and face region extraction), as well as the detection of the nose, eyes, and smile among the facial features with optical enhancement in selected environments. The experimental results show that each detection part has achieved certain recognition rate and recognition time results. The achievements of this research point out the direction for the subsequent optimization of face recognition technology, contribute to its further development and innovation in multiple fields, and help promote its application in more areas. © 2025 SPIE.

关键词： image enhancement

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Research on X-ray weld seam image quality evaluation methods 4

Research on X-ray weld seam image quality evaluation methods

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4th International conference on Signal processing and Computer Science, SPCS 2023

作者： Wang, Ruifeng Gao, Weixin Deng, Guohao Xiao, Yang Li, Yuqing School of Electronic Engineering Xi'an Shiyou University Shaanxi Xi'an710065 China

ISBN: (纸本)9781510672505

The automatic assessment of X-ray weld image quality is an important basis for the automatic assessment of weld image defects. For ring weld X-ray welds, inspectors judge the image quality through human vision and physical blackness meter, which can easily lead to staff fatigue and thus misjudgment, to achieve an automatic assessment of X-ray weld image quality, this paper combines the subjective evaluation results with objective evaluation algorithms to propose a digital blackness meter model suitable for automatic assessment calculations, and gives the ring weld quality assessment algorithm The results show that the sensitivity of the proposed method can reach 98%. The results show that the proposed method has a sensitivity of 98. 5% and a specificity of 100%. © 2023 SPIE.

关键词： Densitometers

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Research on the stability and security of image recognition detection technology for electrical equipment based on cloud-side-end collaboration

Research on the stability and security of image recognition ...

引用

2023 International conference on image, Signal processing, and Pattern Recognition, ISPP 2023

作者： Wu, Fei Qian, Jian Huang, Jianye Li, Yangdi Yang, Yan He, Deming Zheng, Zhou State Grid Fujian Electric Power Co. Ltd. China

ISBN: (纸本)9781510666351

The digital construction process of power grid often uses image intelligent recognition technology in the transmission and substation system for equipment environment monitoring, unmanned inspection and other scenarios, and this process generates massive data, and the existing centralized data processing model is limited by the lack of storage resources and computing power, and cannot meet the massive data processing requirements and frequent interaction needs. In this regard, this paper proposes a framework for the application of image recognition data of side electrical equipment based on cloud-side - end collaboration, and builds an online intelligent diagnosis and analysis model of electrical equipment based on image recognition algorithm, so as to achieve real-time tracking of the operation status of electrical equipment. To further verify the stability and safety of the built model, Matlab simulation software is applied to conduct a targeted case analysis of the model, and the superiority of the proposed cloud-side synergy in the image recognition model of electrical equipment is verified through the comparative analysis of data synergy efficiency curves, which proves the feasibility of the proposed design scheme. © 2023 SPIE.

关键词： image recognition

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Semi-supervised classification method for PolSAR Based on vision transformer (ViT) 4

Semi-supervised classification method for PolSAR Based on vi...

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4th International conference on Signal image processing and Communication, ICSIPC 2024

作者： Li, Xiangshen Yu, Jie Han, Lihua College of Resource Environment and Tourism Capital Normal University Beijing100048 China Beijing Laboratory of Water Resources Security Capital Normal University Beijing100048 China State Key Laboratory Incubation Base of Urban Environmental Process and Digital Simulation Capital Normal University Beijing100048 China Land Satellite Remote Sensing Application Center of MNR Beijing100048 China

ISBN: (纸本)9781510682467

Semi-supervised classification methods generate pseudo-labels from unlabeled data, where pseudo-labels' precisio n is vital for successful classification outcomes. Addressing the challenge of inaccuracies in pseudo-label catego ries during training, this paper introduces a semi-supervised classification strategy for PolSAR images, leveragin g the Vision Transformer (ViT) technology. In this study, the Simple Linear Iterative Clustering (SLIC) method was applied to create superpixel blocks with distinct boundaries and organized structures, facilitating the generat ion of pseudo-labels with a correctness rate of 85.9%. This paper introduces the Vision Transformer (ViT) net work, capitalizing on its multi-head attention mechanism. This approach enhances global image information extr action while simultaneously addressing local details for pseudo-label training. Specifically, on the Flevoland data set, an increase in pseudo-label category accuracy of 7.09% and 5.47% was achieved. For the Wuhan Tongshu n River dataset, improvements of 2.44% and 3.41% in pseudo-label category accuracy were recorded, thereby e levating the precision of PolSAR semi-supervised classification. © 2024 SPIE.

关键词： image enhancement

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Research and Exploration of digital Watermarking Technology Based on BP Neural Network

Research and Exploration of Digital Watermarking Technology ...

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2023 International conference on Electronic Information Engineering and Data processing, EIEDP 2023

作者： Chen, Jiayan Department of Computer and Communication Lanzhou University of Technology Gansu Lanzhou730050 China

ISBN: (纸本)9781510666160

digital watermarking is a technique to embed specific digital signals into digital products to protect copyright integrity, which is an effective way to protect information security. Neural network technology is a mathematical model generation technology that mimics the structural function of biological neural networks and has good self-learning and merit-seeking capabilities. It is feasible to add neural network to digital watermarking technology for copyright protection research. In this paper, we select and improve a generative adversarial network from a classical neural network to generate adversarial samples required for subsequent research using watermarked datasets, where the improvements include combining high-level loss and low-level feature loss,and using adversarial labels to facilitate adversarial classification. The improved generated adversarial samples have the advantage of less alteration to the original image. In this paper, new digital mosaic techniques combined with neural networks are explored in depth rain for new big data directions, which are informative for new areas of research. © 2023 SPIE.

关键词： Neural networks

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