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共 11503 条记录，以下是491-500 订阅

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Low-Light Aerial image Enhancement Algorithm Based on Retinex Theory 2

Low-Light Aerial Image Enhancement Algorithm Based on Retine...

引用

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

作者： Ma, Chenying Xu, Cheng Zhou, Peng Zhang, Yaze Nanjing University of Aeronautics and Astronautics School of Electronic and Information Engineering Nanjing China Nanjing University of Aeronautics and Astronautics School of Astronautics Nanjing China

ISBN: (纸本)9798350331417

The existing low-light image enhancement algorithms are ineffective for UAV aerial images due to challenges such as mountain shading and insufficient illumination during cloud imaging. To overcome these challenges, we propose a reflection image enhancement algorithm based on the principles of Retinex theory, integrating illumination estimation networks and attention mechanisms. This approach improves the quality of aerial images with uneven illumination while avoiding overexposure. We employ a lightweight convolutional neural network to estimate low-light image illumination and enhance reflection images. Furthermore, we incorporate an attention mechanism into the reflection image enhancement process to mitigate overexposure and reduce noise. Experimental results confirm the effectiveness of the proposed image enhancement method in mitigating image degradation caused by mountain shading and inadequate illumination during cloud imaging, consequently improving the quality of UAV-captured aerial images. © 2023 IEEE.

关键词： attention mechanism illumination estimation low-light image enhancement reflection image enhancement Retinex theory

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Extending an Industrial Robot with image processing System 4th

Extending an Industrial Robot with Image Processing System

引用

4th International conference on Vehicle and Automotive Engineering (VAE)

作者： Lenart, Jozsef Univ Miskolc H-3515 Egyet Varos Miskolc Hungary

ISBN: (纸本)9783031152115;9783031152108

Today, industrial robots play a significant role in the automotive industry. There are several workflows in the industry that can only be solved efficiently and productively with robots. These robots are equipped with various accessories, such as grippers, sensors and, if necessary, an image processing system. There are tasks where traditional robot programming with fixed coordinates is not enough;visual information about the workspace and workpiece is needed. The problem, especially in smaller companies, is that the existing robot needs to be upgraded, for example, with a visual sensor and an image processing system, but this is usually difficult and costly for older robots and robot controllers. The aim of my research is to create a solution that allows a robot controller to be economically equipped with an image processing system that is not prepared for this at the factory. All that is required for the controller to be able to communicate with the outside world via some communication interface. An external image processing system, which can be a standard PC with the appropriate camera and software, is required. The image processing software running on the PC communicates with the robot controller, and the robot program receives the necessary information from the image processing system via the communication channel.

关键词： Robotics machine vision image processing

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Transformer-Based Tensor Nuclear Norm for Multi-Dimensional image Completion 2

Transformer-Based Tensor Nuclear Norm for Multi-Dimensional ...

引用

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

作者： Yang, Guowei Jiang, Taixiang Southwestern University of Finance and Economics School of Computer and Artificial Intelligence Chengdu China

ISBN: (纸本)9798350331417

Multi-dimensional image recovery aims to estimate the original high-quality image from the degraded data, which is one of the fundamental problems in image processing. Recently transform-based tensor nuclear norm minimization methods have received widespread attention. These methods primarily involve applying a linear transform to the third mode of a third-order tensor and subsequently performing tensor nuclear norm minimization on the transformed tensor. This process enables the recovery of the underlying low-rank tensor. This paper introduces a Transformer-based neural network that learns a non-linear transform from observed tensors through self-supervision. The network utilizes the low-rank representation of the transformed tensor and employs data fitting between the observed tensor and the reconstructed tensor during the process of self-supervised learning. This approach enables the adaptive construction of a nonlinear transform. The attention mechanism of Transformer ensures a better preserving of the third-dimensional features in the transform. Extensive experimental results confirm that the proposed method outperforms existing multi-dimensional image recovery methods and achieves better results. © 2023 IEEE.

关键词： component Multi-dimensional image Nonlinear transform Self-supervised Tensor nuclear norm Transformer

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SpecRef: A Fast Training-free Baseline of Specific Reference-Condition Real image Editing 2

SpecRef: A Fast Training-free Baseline of Specific Reference...

引用

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

作者： Chen, Songyan Huang, Jiancheng Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350331417

Text-conditional image editing based on large diffusion generative model has attracted the attention of both the industry and the research community. Most existing methods are non-reference editing, with the user only able to provide a source image and text prompt. However, it restricts user's control over the characteristics of editing outcome. To increase user freedom, we propose a new task called Specific Reference Condition Real image Editing, which allows user to provide a reference image to further control the outcome, such as replacing an object with a particular one. To accomplish this, we propose a fast baseline method named SpecRef. Specifically, we design a Specific Reference Attention Controller to incorporate features from the reference image, and adopt a mask mechanism to prevent interference between editing and non-editing regions. We evaluate SpecRef on typical editing tasks and show that it can achieve satisfactory performance. The source code is available on https://***/jingjiqinggong/specp2p. © 2023 IEEE.

关键词： AIGC diffusion model large generative model real image editing text-to-image generation

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Research on High Precision image Registration Method Based on Line Segment Feature and ICP Algorithm

Research on High Precision Image Registration Method Based o...

引用

2023 International conference on Optics and machine vision, ICOMV 2023

作者： Zhang, Di Wei, Hu Huang, Xuan Ni, Huasheng Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9781510664777

image registration is an important research content in image processing technology. Aiming at the problem that traditional registration methods are difficult to accurately register low-texture images, this paper proposes a high-precision image registration algorithm based on line segment features. For the case of wrong match, using the RANSAC random consistent sampling algorithm when searching for the transformation model, and then iterate the nearest points through ICP to transform the parameters further accurately. From the experimental results, the image registration method proposed in this paper is robust to scale, rotation, and illumination and the registration accuracy is improved. © 2023 SPIE. All rights reserved.

关键词： image registration

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Detection of Fault Features in Remanufacturing of Automotive Components Using image processing and Computer vision Techniques 1

引用

4th International conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023

作者： Abdalla, Ibrahim Sakundarini, Novita May May, Christina Chin Chandesa, Tissa Department of Mechanical Materials and Manufacturing Engineering University of Nottingham Malaysia Semenyih Malaysia School of Computer Science University of Nottingham Malaysia Semenyih Malaysia

ISBN: (数字)9789819988198

ISBN: (纸本)9789819988181

Remanufacturing of automotive components involves restoring cores from end-of-life vehicles (ELV) to a condition where the component can be used again. Implementing image processing technique in the visual inspection stage is used to reduce cost and time while increasing accuracy. This research aims to perform real-time surface visual defect detection that is simpler and less costly which commonly uses machine learning and/or deep learning techniques. The methods used in this research are a combination of image processing and computer vision techniques to great effect. The techniques used are a pixel-based contour detection and image subtraction. For this research, connecting will be the sample component to test the algorithm. This approach will take less time to train since it compares the non-defective connecting rod image with the defective connecting rod. The defects that are tested in this research are cracks and buckles, which commonly occur in connecting rod failure due to high load and stress. There are different settings of threshold and illumination that were tested, such as different thresholds of 50, 60, and 70, also illumination colour temperatures such as white, natural, and warm. After 270 trials with different settings and defects, the proposed algorithm achieved a 93% accuracy using a 70 per cent threshold and white light (3000–3500 K). The findings suggest that the implementation of a pixel-based contour detection through image subtraction holds promise as a cost-effective alternative to utilizing machine learning and/or deep learning techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cost effectiveness

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Intelligent Detection Scheme Design of Crucial Components of High Speed Train Bogie Based on machine vision 7

Intelligent Detection Scheme Design of Crucial Components of...

引用

7th IEEE International conference on Information Systems and Computer Aided Education, ICISCAE 2024

作者： Mao, Kaimin Mo, Lingfeng Zhan, Haitao Jia, Shengbo Yang, Yanzhu CRRC Guangdong Co. Ltd Jiangmen China Donghua University Shanghai China

ISBN: (纸本)9798350350760

In the repair and maintenance of the high-speed train bogie, how to configure the intelligent detection device in the bogie workshop to replace the manual heavy and tedious detection has always been a difficult point. This paper puts forward a method based on machine vision and image processing, combined with the actual project, the critical parts of the high-speed train bogie detection. The detection technology is summarized to a certain extent, compared with the long-term artificial naked eye detection, solving the various problems caused by artificial detection, the realization of real-time data collection, and online monitoring. And the measurement results can be timely told to the workers for feedback, significantly improving detection efficiency, to achieve rapid, efficient, and accurate detection. ©2024 IEEE.

关键词： Bogies (railroad rolling stock)

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machine vision-based automatic levels compensation error verification

Machine vision-based automatic levels compensation error ver...

引用

2022 International conference on Precision Instruments and Optical Engineering, PIOE 2022

作者： Wang, Yucheng Liu, Haibo Institute of Seismology China Earthquake Administration No. 40 Hongshan Side Road Hubei Wuhan China

ISBN: (纸本)9781510662902

Algorithms for locating the center position of the crosshair image are studied, and a method based on machine vision to verify the compensation error of automatic levels is proposed. An illumination device is added behind the reticle of the automatic level. The reticle image is focused to infinity, imaged on the focal plane of the lens of the collimator, and images are captured using a CCD camera. Moreover, the necessary processing is performed to locate the center position of the crosshair image by the gray squared center of gravity method and the iterative weighted fitting method to obtain the subpixel level position coordinates. The metrological verification of the compensation error is completed after calibrating the angular grid values of the CCD in the x and y directions, the error angles of the x and y axes, and the parameters of the collimator coordinate system and attitude. The experimental results show that the machine vision-based method meets the requirements of the metrological verification of the compensation error of automatic levels, and the accuracy of the measurement results is higher than the traditional optical method. © 2023 SPIE.

关键词： Error compensation

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Cross-modal Short Video Recommendation

Cross-modal Short Video Recommendation

引用

2023 International conference on machine vision, image processing and Imaging Technology, MVIPIT 2023

作者： Wan, Zhitao Xu, Yuanwei Yang, Miao Hua, Xiuping University of Nottingham Ningbo China and Ningbo Free Trade Zone Blockchain Laboratory Ningbo China Nottingham University Business School China University of Nottingham Ningbo China Ningbo China

ISBN: (纸本)9798350306545

With the rapid development of short video platforms, providing accurate short video recommendations for users has become increasingly important. However, due to the multimodal nature of short videos, effectively utilizing this information to improve recommendation quality remains challenging. This paper proposes a cross-modal short video recommendation method that comprehensively utilizes text, image, and audio information. The method involves multimodal processing of short videos, including segmentation of text, image, and audio, and multimodal alignment. It extracts multimodal features of short videos and fuses these features into a unified short video representation. Recommendations are made based on the similarity between user profiles created from their text browsing history and the short video representations. Finally, a cultural short video recommendation experiment based on users' text reading history is presented. Experimental results show that the cross-modal feature-based recommendation can effectively improve the personalized recommendation accuracy for users in other modalities, especially for cold start users. The proposed method outperforms existing methods in terms of accuracy, recall, and other metrics. © 2023 IEEE.

关键词： image segmentation

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Error Motion Tracking Method for Athletes Based on Multi Eye machine vision 7th

Error Motion Tracking Method for Athletes Based on Multi Eye...

引用

7th EAI International conference on Advanced Hybrid Information processing, ADHIP 2023

作者： Huang, Yanlan Su, Chunshou Guangxi College for Preschool Education Nanning530022 China Yulin Normal University Yulin537000 China

ISBN: (纸本)9783031505515

Traditional methods are unable to perform three-dimensional detection of erroneous movements, resulting in insufficient accuracy in tracking athlete erroneous movements. Therefore, the tracking method for athlete erroneous movements based on multi eye machine vision is highlighted. Using multi eye machine vision technology to construct an athlete error motion tracking framework and obtain athlete error motion image timing. From the perspective of regional consistency and similarity, segment machine vision images of athlete’s incorrect actions. Apply Canny operator to detect athlete’s incorrect actions, obtain pixel values of edge images, and remove false edges. The design is based on a multi eye machine vision athlete error action recognition process, obtaining unknown vectors. With the support of a multi eye machine vision detection system, the absolute value of brightness difference between two frames of images is calculated, and the Hom Schunck algorithm is combined to track the optical flow field to achieve athlete error action tracking. From the experimental verification results, it can be seen that the tracking curve of this method for three types of erroneous actions is consistent with the actual curve, and the maximum tracking accuracy is 93%, which can accurately track athlete’s erroneous actions. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Errors

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