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Research and Design of Weld Seam Tracking Algorithm Based on machine vision and machine Learning 5

Research and Design of Weld Seam Tracking Algorithm Based on...

引用

5th IEEE International conference on Power, Intelligent Computing and Systems, ICPICS 2023

作者： Xu, Wenhao School of Information Engineering Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350333442

This paper proposes an automatic weld seam tracking method based on laser vision and machine learning. The method comprises three main aspects: 1. Utilizing laser vision to obtain two-dimensional laser stripe images for quick acquisition of weld seam position information;2. Implementing deep learning networks to perform image denoising processing, thereby eliminating the impact of noise (such as arc light and spatter) on weld seam feature extraction;3. Using laser triangulation to detect weld points in real-time, thus improving the localization accuracy of the weld tracking process. The paper describes the image denoising method based on an improved Neighbor2Neighbor network, the laser streak target detection and tracking method based on the KCF tracking algorithm, and the weld point extraction method and real-time target tracking method. Corresponding experimental results and flowcharts are provided to verify the effectiveness and feasibility of the proposed method. © 2023 IEEE.

关键词： Welds

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Research and Application of machine vision Based on Beef Carcass Rating Photography Equipment and System

Research and Application of Machine Vision Based on Beef Car...

引用

2024 International conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhu, He Ren, Yichen Gao, Tianyu Xing, Yanxia Shandong Agriculture and Engineering University Jinan China

ISBN: (纸本)9798331527624

Beef, as the pride of meat, is one of the main meat products consumed by the Chinese people. With the continuous rise of national consumption level, people's demand for the quality of beef is also increasing. Due to the late start of China's beef industry, which is mainly composed of regular beef, it is not conducive to building a high-end beef market[3]. In order to improve the efficiency and accuracy of beef carcass detection process and enhance market competitiveness, this paper designs a machine vision based image acquisition device for beef carcass rating. The image is collected under opaque conditions, and the collected image is based on the basic principle of RGB-HSV color model. The RBG value of the measured sample is converted into HSV value for data processing. Then, the data is observed for any patterns and linear equations are summarized. There are significant differences in the analysis of RGB-HSV color models for beef of different grades, thus completing the grading detection of beef. © 2024 IEEE.

关键词： RGB color model

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A machine Learning Approach to image Inpainting 1

引用

14th International conference on Soft Computing and Pattern Recognition, SoCPaR 2022, and the 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2022

作者： Naveenkumar, T. Kulkarni, Harsha Kulkarni, Makrand Raghavendra, H. Guru Jayashree, R. Department of CSE PES University Bengaluru India

ISBN: (数字)9783031275241

ISBN: (纸本)9783031275234

Although image inpainting, or the art of restoring old and degraded photographs/images, has been around for a long time, it has lately acquired popularity as a consequence of technical advancements in image processing technologies. Because of the developments in image processing tools and the versatility of picture editing, automatic image inpainting has become a significant and demanding subject in image processing analysis, with important applications in computer vision. The goal of this article is to develop a hybrid inpainting model that could outperform existing methods. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

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Contrastive Swin-UNet for Unpaired image-to-image Scene Translation 3

Contrastive Swin-UNet for Unpaired Image-to-Image Scene Tran...

引用

3rd International conference on image processing, Computer vision and machine Learning, ICICML 2024

作者： Gunawan, Bryan Li, Xuesong Ge, Penghui Lai, Jie School of Mechanical Engineering Shanghai Jiao Tong University China Shanghai Utopilot Technology Co. Ltd Utopilot AI Shanghai China

ISBN: (纸本)9798350355413

Unpaired image-to-image translation is a challenging task that requires mapping between source and target domains without paired examples. Conventional approaches rely on convolutional neural networks (CNNs) and their variants to achieve reliable translation results. However, in applications where structural consistency is key, CNN-based models are unable to capture global and long-range dependencies. In this paper, we introduce Contrastive Swin-UNet, a framework that leverages contrastive learning with shifted window self-attention mechanism, structured in U-shaped encoder-decoder network. Our approach employs a fully transformer-based generation for effective local and global feature learning. Taking advantage of self-attention, we show that integrated contrastive loss significantly improves translation consistency and generative fidelity by maximizing mutual information between source image and translated output. Our findings indicate that Contrastive Swin-UNet sets a new benchmark for unpaired image-to-image translation tasks, particularly in scenarios requiring high precision and regularity. © 2024 IEEE.

关键词： image-to-image swin unet unpaired vision transformer

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Research on the surface topography inspection of sandpaper based on machine vision 3

Research on the surface topography inspection of sandpaper b...

引用

3rd International conference on Innovations and Development of Information Technologies and Robotics, IDITR 2024

作者： Zheng, Huifeng Liu, Jinru Chen, Ge Xiao, Lei College of Mechanical Engineering Donghua University Shanghai China

ISBN: (纸本)9798350385694

To solve the problems of low efficiency and high subjectivity of existing sandpaper morphology parameter detection methods, machine vision methods are used to detect the surface morphology characteristics of sandpaper. A weighted decision matrix is established to select the important parameters that can reflect the topography of the sandpaper surface;Zeiss Smartproof5 fast turntable confocal microscope equipment is used to obtain the true-color view of different sandpaper samples, the pseudo-color view based on the height, and the XYZ three-dimensional point cloud of the sandpaper surface;the image is preprocessed by the methods of threshold segmentation and morphology processing, and then segmented by watershed segmentation;and the key topographic parameters of different sandpaper samples are calculated and compared. The key morphological parameters of different sandpaper samples were calculated and compared. The results show that the number of abrasive grains, abrasive grain size and other parameters increase with the increase of mesh size, while the uniformity of sandpaper distribution decreases with the increase of mesh size. The results of this study can provide a theoretical reference for the realization of automated inspection of sandpaper surface topography. © 2024 IEEE.

关键词： Computer vision

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Development of Automotive Components Detection Experiment System Based on machine vision 5

Development of Automotive Components Detection Experiment Sy...

引用

5th International conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Li, XueJun Li, LiYan Zhang, LiYing Pan, Dong Yu, ShuYou Wang, JiYu Changchun Humanities and Science College ChangChun China Key Laboratory of Industrial Internet of Things and Networked Control China Jilin University ChangChun China Changchun Up Optotech Co. Ltd ChangChun China

ISBN: (纸本)9798350357950

Automatic detection technology based on machine vision is one of the key technologies in intelligent manufacturing. To meet the demand of the online automatic detection of automotive components, a machine vision-based detection system is designed. The system is composed of machine vision, PLC control, and component transfer and control etc module. The system integrates typical enterprise engineering projects such as automotive components detection based on machine vision into practical teaching, and enables practical projects such as PLC comprehensive training, machine vision and digital image processing algorithms. The system integrates automatic detection technology based on both PLC and machine vision technology, effectively meeting the demand for automatic online detection of automotive components. © 2023 IEEE.

关键词： Automotive components Experimental platform machine vision PLC control

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An Analysis on Virtual Mouse Control using Human Eye 5

An Analysis on Virtual Mouse Control using Human Eye

引用

5th International conference on image processing and Capsule Networks, ICIPCN 2024

作者： Naidu, P.M. Muthukumaran, N. Chandralekha, S. Reddy, K. Tejaswini Vaishnavi, K.Sri India Sri Eshwar College of Engineering Centre for Computational Imaging and Machine Vision Department of ECE Coimbatore India

ISBN: (纸本)9798350367171

Technological advances have enabled hands-free computer interaction, especially for people with limited hand function, such as amputees and paraplegics. However, current solutions face limitations in terms of input methods, accuracy, functionality, and accessibility. The proposed model aims to solve these problems by developing a reliable, user-friendly, and accurate system by utilizing facial expressions, especially eye and mouth movements. The proposed system aims to improve reliability and expressiveness by combining two modalities. Using advanced image processing technology, errors caused by lighting changes are minimized to provide a smooth user experience. The virtual mouse interface provides comprehensive features such as scrolling, clicking, and typing, improving the experience of users with different needs. By providing a reliable, versatile, and convenient hands-free interaction system, this study aims to give users greater independence, improve communication, and increase their participation in the digital world. © 2024 IEEE.

关键词： Eye movements

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GLCM-1DCNN-based hyperspectral inversion of organic matter in improved saline soils 2

GLCM-1DCNN-based hyperspectral inversion of organic matter i...

引用

2nd International conference on image processing, Computer vision and machine Learning, ICICML 2023

作者： Jiang, Yedong Xiao, Zhiyun Inner Mongolia University of Technology College of Electric Power Hohhot China Inner Mongolia Key Laboratory of Mechatronic Control Hohhot China

ISBN: (纸本)9798350331417

The organic matter content of saline soils is an important biochemical indicator for evaluating the effectiveness of saline land improvement. Therefore, monitoring soil organic matter content rapidly and accurately is the key to realizing accurate monitoring of the degree of saline soil improvement. Hyperspectral image technology allows rapid inversion of soil organic matter *** measured hyperspectral data and soil organic matter content of saline-amended soils as raw data and extraction of spatial information by GLCM to form texture features fused with hyperspectral reflectance mapping. Construction of a convolutional network model and inversion of soil organic matter content in saline-amended soils and comparison with hyperspectral reflectance data processing. The results show that compared to other data processing methods, the best prediction model is inverted using the inversion of the texture features extracted with GLCM fused with the hyperspectral reflectance maps, the method of image and spectrum fusion, with is 0.9869, which is a 9.85% enhancement compared to the hyperspectral reflectance inversion method, and is 9.7192, which is a decrease of 65.9210 compared to the hyperspectral reflectance inversion method. © 2023 IEEE.

关键词： Convolutional networks Hyperspectral image and spectrum fusion Organic matter content Saline soil

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Semantic Preprocessor for image Compression for machines 48

Semantic Preprocessor for Image Compression for Machines

引用

48th IEEE International conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Yang, Mingyi Herranz, Luis Yang, Fei Murn, Luka Blanch, Marc Gorriz Wan, Shuai Yang, Fuzheng Mrak, Marta Xidian University School of Telecommunications Engineering Xi'an China Computer Vision Center Barcelona Spain Universitat Autònoma de Barcelona Barcelona Spain BBC Research & Development London United Kingdom Northwestern Polytechnical University School of Electronics and Information Xi'an China

ISBN: (纸本)9781728163277

Visual content is being increasingly transmitted and consumed by machines rather than humans to perform automated content analysis tasks. In this paper, we propose an image preprocessor that optimizes the input image for machine consumption prior to encoding by an off-the-shelf codec designed for human consumption. To achieve a better trade-off between the accuracy of the machine analysis task and bitrate, we propose leveraging pre-extracted semantic information to improve the preprocessor's ability to accurately identify and filter out task-irrelevant information. Furthermore, we propose a two-part loss function to optimize the preprocessor, consisted of a rate-task performance loss and a semantic distillation loss, which helps the reconstructed image obtain more information that contributes to the accuracy of the task. Experiments show that the proposed preprocessor can save up to 48.83% bitrate compared with the method without the preprocessor, and save up to 36.24% bitrate compared to existing preprocessors for machine vision. © 2023 IEEE.

关键词： Semantics

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Maritime image Stabilization: A Comprehensive Review of Techniques and Challenges 9

Maritime Image Stabilization: A Comprehensive Review of Tech...

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9th International conference on Electronic Technology and Information Science (ICETIS)

作者： Wei, Enping Tan, Yong Chai Tai, Vin Cent Hao, Yanan Zhang, Xiaodong Zhang, Tian SEGI Univ Fac Engn Built Environm & Informat Technol Ctr Modelling & Simulat Kuala Lumpur Malaysia

ISBN: (纸本)9798350388350;9798350388343

image stabilization plays a crucial role in providing accurate and reliable visual information for machine vision applications. In maritime applications, such as unmanned ship navigation, where six degrees of freedom (DOF) motion and harsh maritime conditions prevail, the efficacy of image stabilization technology is vital for robust image processing algorithms. This paper offers a comprehensive review of image stabilization techniques tailored for maritime environments, developed over the past two decades. We analyzed a total of 39 research articles on the subject, sourced from Web-of-Science, SCOPUS, and the Engineering Index databases, discussing potential research directions to address the limitations of current image stabilization methods, with special consideration for the unique requirements of ship-borne cameras. It provides an up-to-date overview of the techniques, limitations, and algorithms of ship-borne cameras for maritime applications, identifying current knowledge gaps and areas requiring further research. This review aims to guide the development of new technologies and methods to improve the performance of image stabilization systems in maritime contexts.

关键词： image Stabilization Assessment Application Maritime Environment Ship-borne Camera

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