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3rd International Conference on Electronics and Communication and Aerospace Technology, ICECA 2019

作者： Barhate, Deepti Nemade, Varsha Computer Department MPSTME SVKM's NMIMS Shirpur Maharashtra India

ISBN: (纸本)9781728101675

In Field of agriculture, the cultural manual inspection remains as a slow and tedious work along with the high error factor, in order to overcome this problem, this research work illustrates the different techniques used to initiate automated robots to perform the agricultural task. Intelligent system is required for cultivation, and harvesting of crops, which can identify the crops according to its features, margin, and colour. As the need of agriculture is automation, Information technology and robotics for harvesting. This paper is the study of various technologies of robotics for cultivation. This paper shows how different robots work in the field of agriculture for capturing the fruits, cultivation of cotton, identification of weed and crops etc. by using the Machine learning, Convolutional Neural network(CNN), and multilayer preceptor. Further the study shows that the fruit detection was done by trained algorithm of image processing with extraction of only the required features. The colour, shape, margin, texture was provided as the input test *** main goal of this paper is to develop an automated fruit recognition and picker system using the laser sensor and machine vision that remains similar to that of human picker. In the field of agriculture, the cultural manual inspection remains as a slow and tedious work along with high error factor. To overcome this problem this paper shows the different techniques used to make the automated robots to perform the agricultural task. The intelligent system is required for cultivation, and harvesting of crops in order to identify the crops according to its features, margin, and colour. © 2019 IEEE.

关键词： Crops

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ALGORITHMS FOR THE AUTOMATIC DETECTION AND CHARACTERIZATION OF PATHOLOGIES IN HERITAGE ELEMENTS FROM THERMOGRAPHIC imageS 27

ALGORITHMS FOR THE AUTOMATIC DETECTION AND CHARACTERIZATION ...

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27th CIPA International Symposium on Documenting the Past for a Better Future

作者： Garrido, I. Laguela, S. Sfarra, S. Solla, M. Univ Vigo Min & Energy Engn Sch Appl Geotechnol Res Grp Rua Maxwell S-N Vigo 36310 Spain Univ Salamanca EPS Avila TIDOP Res Grp Calle Hornos Caleros 50 Avila 05003 Spain Univ Aquila Dept Ind & Informat Engn & Econ DIIIE Piazzale E Pontieri 1 I-67100 Laquila Italy Spanish Naval Acad Def Univ Ctr Plaza Espana S-N Marin 36920 Spain

Heritage elements, from historic buildings to stone sculptures and panels, stand as key elements in the history of humanity. Unfortunately, the deterioration of both the surface and the interior of these elements is inevitable, endangering the quality and existence of these structures of high historical value in the event of a delay in the implementation of the required maintenance tasks. InfraRed Thermography, IRT, appears as one of the most recent techniques to detect and characterize possible pathologies in structures in their early stages, being very useful for a preventive analysis in heritage elements. This paper presents a methodology for the automatic detection and characterization of one of the most severe and frequent pathologies in heritage structures, moisture, from thermal images. The proposal stands as a demonstration of the potential of the IRT technique for heritage conservation applications, and as a new step towards the automation of the inspection process and optimization of the decision-taking in conservation actions within cultural heritage. For that, two thermal criteria and a semiautomatic image rectification process are implemented as main phases of the methodology, obtaining good results for the detection of moisture zones and accurate area values with regard to the real dimensions of each moisture zone. Specifically, an F-score average of 78%+/- 19% regarding detection performance and a percentage relative error of minimum 4%, and maximum of 12%, referred to the area computation in unit metrics are obtained.

关键词： heritage conservation moisture InfraRed Thermography automation image processing

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Non-destructive testing and evaluation of composite materials/structures: A state-of-the-art review

arXiv

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arXiv 2020年

作者： Wang, Bing Zhong, Shuncong Lee, Tung-Lik Fancey, Kevin S. Mi, Jiawei Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom School of Mechanical Engineering and Automation Fuzhou University Fuzhou350116 China ISIS Neutron and Muon Source Rutherford Appleton Laboratory Harwell Oxford DidcotOX11 0QX United Kingdom Department of Engineering University of Hull HullHU6 7RX United Kingdom

Composite materials/structures are advancing in product efficiency, cost-effectiveness and the development of superior specific properties. There are increasing demands in their applications to load-carrying structures in aerospace, wind turbines, transportation, and medical equipment, etc. Thus robust and reliable non-destructive testing (NDT) of composites is essential to reduce safety concerns and maintenance costs. There have been various NDT methods built upon different principles for quality assurance during the whole lifecycle of a composite product. This paper reviews the most established NDT techniques for detection and evaluation of defects/damage evolution in composites. These include acoustic emission, ultrasonic testing, infrared thermography, terahertz testing, shearography, digital image correlation, as well as X-ray and neutron imaging. For each NDT technique, we cover a brief historical background, principles, standard practices, equipment and facilities used for composite research. We also compare and discuss their benefits and limitations, and further summarise their capabilities and applications to composite structures. Each NDT technique has its own potential and rarely achieves a full-scale diagnosis of structural integrity. Future development of NDT techniques for composites will be directed towards intelligent and automated inspection systems with high accuracy and efficient data processing capabilities. Copyright © 2020, The Authors. All rights reserved.

关键词： Structural health monitoring

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Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

Early detection, segmentation and quantification of coronary...

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Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and applications

作者： Alam, M.A. Shakir, M.B. Hossain, M.A. Pavel, M.I. Shams, K.M.A. Akib, F.R. Dept. of Computer Science and Engineering BRAC University Dhaka1212 Bangladesh

ISBN: (数字)9781510616486

ISBN: (纸本)9781510616479

This proposed method aims towards a full automation of the detection of coronary artery blockage through some image processing techniques so that the system does not have to rely on human's inspection. The goal of the research is to implement the proposed image processing techniques so the system can detect the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. The research suggests that the system will require a 64-slice CTA image as input. After the acquisition of the desired input image, it will go through several steps to determine the region of interest. This research proposes a two stage approach that includes the preprocessing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of two feature ratios to finally determine the intended result. In order to get more insights of the subject of these examinations, this research has proposed the use of an algorithm to create a 3-D model. © 2018 SPIE.

关键词： image segmentation

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CSPD-DETR: Real-time silicon crystalline photovoltaic cell surface defect detection transformer for building photovoltaic systems

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Journal of Building Engineering 2025年 108卷

作者： Chen, Shouhong Lu, Ying Qin, Guanxiang Hou, Xingna Sun, Yongjian Guangxi Key Laboratory of Automatic Detecting Technology and Instruments School of Electronic Engineering & Automation Guilin University of Electronic Technology Guilin541004 China School of Architecture and Transportation Engineering Guilin University of Electronic Technology Guilin541004 China PLA Army Special Operations Academy Guilin541000 China

Crystalline silicon photovoltaic (PV) cells are essential components in building-integrated photovoltaic (BIPV) systems, where identifying defects is vital to ensure energy efficiency, operational safety, and long-term sustainability of buildings. However, crystalline silicon PV cells exhibit various defects that differ in shape, size, and distribution, with small defects often obscured by background noise or normal structures. Deep learning has shown promising applications in real-world building engineering fields. This study proposes a real-time crystalline silicon PV cell defect DEtection TRansformer (CSPD-DETR) to address the above challenges. It introduces a novel dilated re-parameterized residual block (DRRB), which extracts features with varying receptive field sizes. It also incorporates the inverted residual mobile block to enhance local and global feature modeling. Thus, the inverted residual dilated network (IRD-Net) is designed as the backbone for feature extraction, integrating both the DRRB and the inverted residual mobile block. Additionally, the study proposes a dilated wavelet cross-scale fusion module (DWCSFM) to optimize the encoder. It alternately updates high-level and low-level features, suppresses aliasing, and reduces both the parameter count and computational load. Evaluated on public PV cell defect datasets (ELPV and PVEL-AD), CSPD-DETR achieves mAP@0.5 of 97.7 % and 93.6 %, outperforming state-of-the-art defect detectors. It reduces parameters by 12.37 % compared to the baseline and gets 86.06 FPS, meeting real-time requirements. CSPD-DETR introduces architectural advancements in feature learning and lightweight transformer design, effectively addressing the challenges of complex backgrounds in crystalline silicon photovoltaic EL image defect detection. © 2025 Elsevier Ltd

关键词： Partitions (building)

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基于无人机巡检的极端环境架空输电线路缺陷检测系统

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自动化技术与应用 2025年第2期44卷 52-56页

作者：孙喆周来宏张琰西安电力高等专科学校陕西西安710000 国网陕西省电力有限公司培训中心陕西咸阳712000

针对当前极端环境架空输电线路缺陷检测存在的不足,提高极端环境架空输电线路缺陷检测效果,设计基于无人机巡检的极端环境架空输电线路缺陷检测系统。采集环境数据,传送至无人机伺服模块,电子调速器依据数据调节无人机舵机偏转角度与转... 详细信息

针对当前极端环境架空输电线路缺陷检测存在的不足,提高极端环境架空输电线路缺陷检测效果,设计基于无人机巡检的极端环境架空输电线路缺陷检测系统。采集环境数据,传送至无人机伺服模块,电子调速器依据数据调节无人机舵机偏转角度与转速,采集架空输电线路图像,图像利传送至地面数据处理中心,缺陷检测单元利用基于决策树方法得到缺陷检测结果。实验证明:系统可以有效检测架空输电线路的断线、断股、绝缘子散落等缺陷,提升架空输电线路的运行安全性。

关键词：无人机巡检极端环境架空输电线路缺陷检测系统设计

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机器视觉在输电线路巡检机器人中的应用综述

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自动化技术与应用 2019年第4期38卷 83-87页

作者：成建宏西安工程大学机电工程学院陕西西安710600

输电线路巡检机器人是用于代替传统巡检方式的一种高效的新型巡检技术,机器视觉技术是输电线路巡检机器人研究中的重要内容之一。在介绍机器视觉系统的基础上,结合现有研究成果,详细讨论了输电线路巡检机器人中机器视觉在机器人视觉导... 详细信息

输电线路巡检机器人是用于代替传统巡检方式的一种高效的新型巡检技术,机器视觉技术是输电线路巡检机器人研究中的重要内容之一。在介绍机器视觉系统的基础上,结合现有研究成果,详细讨论了输电线路巡检机器人中机器视觉在机器人视觉导航、视觉伺服控制、视觉检测等方面的应用以及研究现状,最后分析了输电线路巡检机器人视觉系统在摄像头视角适应性、实时性、图像特征选择等方面存在的问题,并给出了相应的下一阶段研究方向的建议。

关键词：机器视觉巡检机器人输电线路图像处理

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Optimal path planning for UAV based inspection system of large-scale photovoltaic farm

Optimal path planning for UAV based inspection system of lar...

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Chinese automation Congress (CAC)

作者： Luo, Xuejing Li, Xiaoxia Yang, Qiang Wu, Fengjie Zhang, Duo Yan, Wenjun Xi, Zhipeng Zhejiang Univ Coll Elect Engn Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781538635247

Small scale quad-rotor unmanned aerial vehicle (UAV) has attracted much attention in recent years and has been widely adopted in many civil applications, e.g. inspection of critical infrastructure spanning over a large geographical area. In a typical UAV based inspection system for large-scale photovoltaic farm, it is required to control the mounted gimbal camera taking pictures of all the PV modules and eventually accurately identify the ones with defects through efficient image processing techniques. Given a series of way points without an effective path generation algorithm, the image acquisition can be not satisfactory and even miss some areas that should be inspected. In this paper, a Bezier curve and particle swarm optimization (PSO) joint approach is presented to address the UAV path planning challenge. The path generation process fully takes flight attitude, gimbal limitation and path length into consideration with the aim to improve the efficiency and the reliability of the inspection system. The performance of the proposed solution is assessed through a set of simulation experiments and the numerical result demonstrates the effectiveness of the proposed optimal path planning solution.

关键词： Quad-rotor UAV PV inspection path planning Bezier curve particle swarm optimization

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automation inspection dimensional and parts of recognition and industrial materials 3

Automation inspection dimensional and parts of recognition a...

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3rd International Conference on Numerical and Symbolic Computation: Developments and applications, SYMCOMP 2017

作者： De Melo, Charles Luiz S. Junior, Almir K. Bastos, Moises P. Manaus Institute of Technology 69088-130 Brazil University of the State of Amazonas Control Engineering and Automation 69020-000 Brazil

ISBN: (纸本)9789899941038

Most industrial visual inspection systems still dealing with a low variety of object classes. This is because even the most recognition techniques and representation scheme are not flexible enough to support major changes in the field of objects to recogni ze and scale. To avoid this type of restriction, our system incorporates digital processing techniques of image, a software able to do all sorts of for recognition and sizing and a fully compatible hardware with all the operational requirem ents of the sof tware. From the analysis of the captured images, our system is able to choose, in a learning phase, the representation scheme best suited for each of the pieces, which facilitates and speeds up the identification and subsequent location of the same in the recognition phase. The advantages of applying these techniques representation were observed in several experiments, both with simulated real images as real-time images. The objective of this article is to describe the implementation of a computer vision system, able to choose the best strategy to recognize measure and locate planar objects, aiming at industrial applications. © ECCOMAS, Portugal.

关键词： Computer vision

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机器视觉在宽幅印刷品在线检测中的应用

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自动化技术与应用 2019年第4期38卷 134-137页

作者：侯战强韩震宇四川大学四川成都610065

介绍了大幅面高速高精度彩色印刷品缺陷在线检测系统、处理流程和检测软件的实际使用情况。介绍了该系统大幅面高速彩色印刷品检测使用的方法和算法,并经过实际应用证明了其有效性。探讨了彩色图像分通道处理的方法。提出了针对大幅面... 详细信息

介绍了大幅面高速高精度彩色印刷品缺陷在线检测系统、处理流程和检测软件的实际使用情况。介绍了该系统大幅面高速彩色印刷品检测使用的方法和算法,并经过实际应用证明了其有效性。探讨了彩色图像分通道处理的方法。提出了针对大幅面高速印刷品检测的一种滤除伪轮廓杂波的算法,并论证了滤除杂波在该类系统中的重要性。

关键词：机器视觉在线检测宽幅印刷品检测分通道处理伪轮廓

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