An effective image fusion algorithm based on grey relation of similarity and morphology
作者：
Caiping Liu;Yahui Long;Jianxu Mao* ;Hui Zhang;Ruizhi Huang;...
期刊：
Journal of Ambient Intelligence and Humanized Computing ,2023年14(11):14859-14872 ISSN：1868-5137
通讯作者：
Jianxu Mao
作者机构：
[Caiping Liu; Yahui Long; Ruizhi Huang] College of Computer Science and Electronic Engineering, Hunan University, Changsha, China;[Jianxu Mao; Yang Dai] College of Electrical and Information Engineering, Hunan University, Changsha, China;[Hui Zhang] College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China
通讯机构：
[Jianxu Mao] C;College of Electrical and Information Engineering, Hunan University, Changsha, China
关键词：
Image fusion;Multi-focus image;Grey relational analysis;Mathematical morphology;Computational complexity
摘要：
Considering the problems of the limited energy in wireless multi-media sensor networks (WMSNs) and the focused regions discontinuity of the fused image obtained using traditional multi-scale analysis tools (MST)-based methods, an effective multi-focus image fusion algorithm is proposed in this paper. In this method, the original fused image is obtained based on wavelet transform where the low-frequency coefficients are fused by average scheme, whereas the high-frequency coefficients are fused by the proposed merging rule consisting of the grey relation analysis of similarity and local area energy. Then, grey absolute relation analysis is again utilized as measurement indicator to estimate the similarities between the initial fused image and source images, during which the initial map is acquired and then corrected by the mathematical morphological opening and closing. Finally, the fused image is obtained with the guidance of the corrected map, namely the decision map. Experiment results demonstrate that the fused image using the proposed algorithm is more continuous in focused region and more similar to source images in brightness compared with state-of-art multi-focus image fusion algorithms, such as Curvelet transform, lifting stationary wavelet transform (LSWT), non-subsampled contourlet transform (NSCT) and non-subsampled shearlet transform (NSST). Meanwhile, the proposed method shows better superiority in term of the computational complexity. © 2018 Springer-Verlag GmbH Germany, part of Springer Nature
语种：
英文
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A Width-Growth Model with Subnetwork Nodes and Refinement Structure for Representation Learning and Image Classification
作者：
Zhang, Wandong;Wu, Q. M. Jonathan* ;Yang, Yimin;Akilan, Thangarajah;Zhang, Hui
期刊：
IEEE Transactions on Industrial Informatics ,2021年17(3):1562-1572 ISSN：1551-3203
通讯作者：
Wu, Q. M. Jonathan
作者机构：
[Zhang, Wandong; Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada.;[Yang, Yimin; Akilan, Thangarajah] Lakehead Univ, Dept Comp Sci, Thunder Bay, ON P7B 5E1, Canada.;[Zhang, Hui] Hunan Univ, Sch Robot, Changsha 410082, Peoples R China.;[Zhang, Hui] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410012, Peoples R China.
通讯机构：
[Wu, Q. M. Jonathan] U;Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada.
关键词：
Encoding;Feature extraction;Informatics;Neural networks;Learning systems;Nonhomogeneous media;Transforms;Feature refinement;image classification;multimodal fusion;representation learning;subnetwork neural network
摘要：
This article presents a new supervised multilayer subnetwork-based feature refinement and classification model for representation learning. The novelties of this algorithm are as follows: 1) different from most multilayer networks that go deeper with increased number of network layers, this work architects a model with wider subnetwork nodes; 2) the conventional classification methods adopt a separate search mechanism to derive a generalized feature space and to get the final cognition, but this work proposes a one-shot process to find the meaningful latent space and recognize the objects; and 3) the traditional feature representation and image classification approaches apply a unimodal feature coding, which suffers from lack of global knowledge. This work overcomes the pitfall through multimodal fusion that fuses various feature sources into one superstate encoding to achieve higher performance. A cross-domain experimental study on camera identification and image classification shows that the proposed method achieves superior performance compared to the existing models.
语种：
英文
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医药智能制造生产线关键技术研究进展
作者：
易俊飞;张辉;赵晨阳;车爱博;王耀南
期刊：
中南大学学报(自然科学版) ,2021年52(02):421-433 ISSN：1672-7207
作者机构：
[赵晨阳; 车爱博; 易俊飞] 长沙理工大学电气与信息工程学院;[王耀南; 张辉] 湖南大学机器人视觉感知与控制技术国家工程实验室
关键词：
医药智能制造生产线;无菌化智能生产;质量检测;柔性抓取;智能搬运;智能协调优化控制
摘要：
医药工业是维系国民健康、关系到国计民生的重要产业,先进的制药装备是提高医药产品生产效率和质量的重要保障。医药智能制造生产线是由无菌化柔性配药机器人、无菌化灌装—转运—封口机器人、医药质量视觉检测机器人、无菌化分拣包装机器人、智能搬运机器人等多智能机器人组成的智能制药系统。本文对医药智能制造生产线的进展进行分析,分别从无菌配药到分拣包装工艺流程中的无菌化智能生产、医药质量检测、柔性抓取与智能搬运以及智能协同优化控制等关键技术进行论述,最后对其发展方向进行展望。
语种：
中文
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A Practical Visual Servo Control for Aerial Manipulation Using a Spherical Projection Model
作者：
Zhong, Hang;Miao, Zhiqiang* ;Wang, Yaonan;Mao, Jianxu;Li, Ling;...
期刊：
IEEE Transactions on Industrial Electronics ,2020年67(12):10564-10574 ISSN：0278-0046
通讯作者：
Miao, Zhiqiang
作者机构：
[Zhong, Hang; Miao, Zhiqiang; Wang, Yaonan; Mao, Jianxu] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China.;[Li, Ling] Changsha Univ Sci & Technol, Engn Training Ctr, Changsha 410114, Peoples R China.;[Zhang, Hui] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410114, Peoples R China.;[Chen, Yanjie] Fuzhou Univ, Sch Mech Engn & Automat, Fuzhou 350116, Peoples R China.;[Fierro, Rafael] Univ New Mexico, Multiagent Robot & Heterogeneous Syst Lab, Dept Elect & Comp Engn, Albuquerque, NM 87131 USA.
通讯机构：
[Miao, Zhiqiang] H;Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China.
关键词：
Manipulators;Visualization;Cameras;Servosystems;Task analysis;Grippers;Aerial manipulation;spherical projection;visual servo
摘要：
This article addresses the problem of autonomous servoing control of an unmanned aerial manipulator with the capability of grasping target objects using computer vision. Specifically, a practical visual servo control using a spherical projection model is proposed. The aerial manipulator is an unmanned aerial vehicle equipped with a robotic arm that greatly increases the freedom and operational flexibility of the end-effector. However, it also increases the complexity of the kinematics, dynamics, and control design of the complete system. A novel passivity-like error equation of the image features is established by using the spherical camera geometry dynamics with an eye-in-hand configuration. To further improve the grasping performance, a task-priority control scheme is utilized with one main task and several subtasks, i.e., controlling the gripper position and orientation, vertically aligning the center of gravity, and avoiding the joint limitation. Simulation results are provided to illustrate and assess the performance of the proposed visual servo control. The practicability and effectiveness of autonomous aerial manipulation are well supported by the experimental results acquired through outdoor environments. © 1982-2012 IEEE.
语种：
英文
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基于改进马尔可夫随机场的钢轨缺陷分割
作者：
张辉;李平;贺振东
期刊：
计算机工程与设计 ,2020年41(4):1052-1061 ISSN：1000-7024
作者机构：
长沙理工大学电气与信息工程学院,湖南长沙 410114;温莎大学电气与计算机工程系,加拿大温莎 N9B3P4;郑州轻工业学院电气信息工程学院,河南郑州450002;[李平; 张辉] 长沙理工大学;[贺振东] 郑州轻工业学院
关键词：
钢轨缺陷;背景差分;马尔可夫随机场;空间信息;缺陷分割
摘要：
为提高钢轨缺陷分割对噪声的鲁棒性,提出一种基于改进马尔可夫随机场(MRF)的钢轨缺陷分割方法.利用背景差分法对灰度进行预处理,消除灰度分布不均的干扰.对模糊if-then规则的前提部分采用马尔可夫随机场来利用图像中的空间约束,结果部分指定像素距离图算法,通过使用马尔可夫随机场(MRF)在相邻像素图像之间并入局部空间信息,推导出新的自适应模糊集和M RF相结合的钢轨表面缺陷自动分割方法.建立标准的FCM、GM M和该方法的钢轨缺陷分割对比实验,验证了算法的有效性和优越性.
语种：
中文
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医药质量检测关键技术及其应用综述
作者：
张辉;易俊飞;王耀南;吴刘宸;陈瑞博
期刊：
仪器仪表学报 ,2020年41(3):1-17 ISSN：0254-3087
通讯作者：
Zhang, Hui(zhanghuihby@126.com)
作者机构：
[张辉; 易俊飞; 吴刘宸; 陈瑞博] College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha;410114, China;[王耀南] National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha;410082, China;[张辉] 410114, China<&wdkj&>National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha
关键词：
医药产品;质量检测;X射线检测技术;高光谱检测技术;机器视觉
摘要：
医药产品种类多样、生产工艺复杂,传统人工检测已不能满足高端医药发展的需求,而迫切需要对医药检测技术进行革新。医药产业是维系国民健康、关涉国计民生的重要产业,故医药质量检测环节必不可少。首先简要介绍了医药检测的对象及标准,重点综述了医药可见异物检测、药物成分检测和包装缺陷等质量检测进展情况,分析了国家药典中多类型药品的现行检测标准。在此基础上,阐述了最新的医药检测关键技术如X射线检测技术、高光谱检测技术、机器视觉的检测技术等,并讨论了医药检测关键技术在多类型药品检测中的应用,最后重点探讨了医药质量检测技术的发展趋势。
语种：
中文
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DM-RIS: Deep multimodel rail inspection system with improved MRF-GMM and CNN
作者：
Jin, Xiating* ;Wang, Yaonan;Zhang, Hui* ;Zhong, Hang;Liu, Li;...
期刊：
IEEE Transactions on Instrumentation and Measurement ,2020年69(4):1051-1065 ISSN：0018-9456
通讯作者：
Jin, Xiating;Zhang, Hui
作者机构：
[Liu, Li; Zhong, Hang; Jin, Xiating; Wang, Yaonan] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.;[Zhang, Hui] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410012, Peoples R China.;[Zhang, Hui] Univ Windsor, Dept Elect & Comp Engn, CVSS Lab, Windsor, ON N9B 3P4, Canada.;[Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada.;[Yang, Yimin] Lakehead Univ, Dept Comp Sci, Thunder Bay, ON P7B 5E1, Canada.
通讯机构：
[Jin, Xiating] H;[Zhang, Hui] C;Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.;Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410012, Peoples R China.
关键词：
Faster RCNN;improved Gaussian mixture model (GMM);Markov random field (MRF);rail inspection;surface defect;visual detection
摘要：
Rail inspection system (RIS) remains an emergent instrumentation for railway transportation, with its capacity of measuring surface defect on steel rail. However, detecting technique and interpretation of RIS constitute a challenging problem since traditional technologies are expensive and prone to errors. In this paper, a deep multimodel RIS (DM-RIS) is established for surface defect where fast and robust spatially constrained Gaussian mixture model is presented for segmentation proposal and Faster RCNN is utilized for objective location in a parallel structure. First, we incorporate spatial information between pixels into an improved Gaussian mixture model based on Markov random field (MRF) for accurate and rapid defect edge segmentation. Specifically, a direct parameter-learning in expectation & x2013;maximization (EM) algorithm is proposed. Meanwhile, to remove nondefect, numerous labeled samples with weak illumination, inequality reflection, external noise, rust, and greasy dirt are fed into Faster RCNN so that DM-RIS is robust environmentally to various light, angle, background, and acquisition equipment. Finally, the joint hit area refers to a real defect. The experimental results demonstrate that the proposed method performs well with 96.74 & x0025; precision, 94.13 & x0025; recall, 95.18 & x0025; overlap, and 0.485 s/frame speed on average, and is robust compared with the related well-established approaches.
语种：
英文
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基于轻量型卷积神经网络的交通标志识别
作者：
龙曼仪;李茂军;张辉;刘芾
期刊：
计算技术与自动化 ,2020年39(04):112-118 ISSN：1003-6199
作者机构：
长沙理工大学电气与信息工程学院,湖南长沙410114;湖南大学机器人学院,湖南长沙410114;[刘芾; 龙曼仪; 李茂军] 长沙理工大学;[张辉] 湖南大学
关键词：
卷积神经网络;交通标识;图像增强;深度可分离卷积;激活函数
摘要：
针对卷积神经网络在交通标志识别实时性不好,对设备硬件要求过高的缺点,提出了一种具有实时性,高精度的基于轻量型卷积神经网络的改进网络。一方面引入深度可分离卷积和激活函数Mish,加快网络的训练和识别速度,降低对硬件设备的要求;另一方面通过对网络架构及层次的改进,同时合理改变卷积核的大小和数目,加强图片特征的表达与传递。在BelgiumTSC交通标志数据集上的实验结果表明,改进后网络明显提高了网络训练速度,同时识别精度也略高于原网络,验证了改进方法的有效性。通过与其他模型相比,该模型能够更快速准确完成交通标志识别任务,验证了该方法的可行性。
语种：
中文
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Deep Multimodel Cascade Method Based on CNN and Random Forest for Pharmaceutical Particle Detection
作者：
Zhang, Hui* ;Zhao, Miao;Liu, Li* ;Zhong, Hang;Liang, Zhicong;...
期刊：
IEEE Transactions on Instrumentation and Measurement ,2020年69(9):7028-7042 ISSN：0018-9456
通讯作者：
Zhang, Hui;Liu, Li
作者机构：
[Zhang, Hui] Hunan Univ, Sch Robot, Changsha 410082, Hunan, Peoples R China.;[Zhang, Hui; Liang, Zhicong; Zhao, Miao] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410012, Peoples R China.;[Liu, Li; Zhong, Hang; Wang, Yaonan; Zhou, Xianen] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.;[Yang, Yimin] Lakehead Univ, Dept Comp Sci, Thunder Bay, ON P7B 5E1, Canada.;[Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada.
通讯机构：
[Zhang, Hui; Liu, Li] H;Hunan Univ, Sch Robot, Changsha 410082, Hunan, Peoples R China.;Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.
关键词：
Faster R-CNN;k-means;moving foreign particles visual detection;pharmaceutical detection;random forest (RF);trajectory space feature vector
摘要：
The quality detection of pharmaceutical liquid products is inevitable and crucial in drug manufacture because drugs contaminated with foreign particles are definitely not to be used. However, with the current detection methods, it is still a challenge to detect and identify the small moving particles using an imaging system. In this article, a deep multimodel cascade method combining single-frame image and multiframe images processing method to detect and identify foreign particles is proposed. The proposed method consists of three stages. First, a Faster R-CNN convolutional neural network is adopted to detect and localize the multiple suspected foreign particles of each single-frame image. Then, the k-means clustering algorithm is used to cluster the trail of that detected multiple suspected foreign particles in the eight sequential images to obtain the moving object trajectory. Finally, trajectory features are extracted and the random forest (RF) classifier is used to distinguish noises and foreign particles according to the motion feature of the moving object trajectory. Experimental results demonstrate that the proposed multitask stepwise method improves the accuracy of foreign particles detection and reduces the rate of omission in the case of strong noise, which proves the effectiveness of this method. © 1963-2012 IEEE.
语种：
英文
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A Surface Defect Detection Framework for Glass Bottle Bottom Using Visual Attention Model and Wavelet Transform
作者：
Zhou, Xianen;Wang, Yaonan;Zhu, Qing;Mao, Jianxu* ;Xiao, Changyan;...
期刊：
IEEE Transactions on Industrial Informatics ,2020年16(4):2189-2201 ISSN：1551-3203
通讯作者：
Mao, Jianxu
作者机构：
[Wang, Yaonan; Mao, Jianxu; Zhou, Xianen; Xiao, Changyan; Zhu, Qing] Hunan Univ, Coll Elect & Informat Engn, Natl Engn Lab Robot Visual Percept & Control Tech, Changsha 410082, Peoples R China.;[Lu, Xiao] Hunan Normal Univ, Coll Engn & Design, Changsha 410081, Peoples R China.;[Zhang, Hui] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410114, Peoples R China.
通讯机构：
[Mao, Jianxu] H;Hunan Univ, Coll Elect & Informat Engn, Natl Engn Lab Robot Visual Percept & Control Tech, Changsha 410082, Peoples R China.
关键词：
Anisotropic diffusion;defect detection;saliency detection;superpixel segmentation;wavelet transform
摘要：
Glass bottles must be thoroughly inspected before they are used for packaging. However, the vision inspection of bottle bottoms for defects remains a challenging task in quality control due to inaccurate localization, the difficulty in detecting defects in the texture region, and the intrinsically nonuniform brightness across the central panel. To overcome these problems, we propose a surface defect detection framework, which is composed of three main parts. First, a new localization method named entropy rate superpixel circle detection (ERSCD), which combines least-squares circle detection and entropy rate superpixel (ERS) with an improved randomized circle detection, is proposed to accurately obtain the region of interest (ROI) of the bottle bottom. Then, according to the structure-property, the ROI is divided into two measurement regions: central panel region and annular texture region. For the former, a defect detection method named frequency-tuned anisotropic diffusion super-pixel segmentation (FTADSP) that integrates frequency-tuned salient region detection (FT), anisotropic diffusion, and an improved superpixel segmentation is proposed to precisely detect the regions and boundaries of defects. For the latter, a defect detection strategy called wavelet transform multiscale filtering (WTMF) based on a wavelet transform and a multiscale filtering algorithm is proposed to reduce the influence of texture and to improve the robustness to localization error. The proposed framework is tested on four data sets obtained by our designed vision system. The experimental results demonstrate that our framework achieves the best performance compared with many traditional methods. © 2005-2012 IEEE.
语种：
英文
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基于PLC的汽车横拉杆拧紧系统的应用与实现
作者：
谭益娜;张辉
期刊：
电子设计工程 ,2020年(05):134-138 ISSN：1674-6236
作者机构：
长沙理工大学电气与信息工程学院
关键词：
转向横拉杆;自动拧紧;伺服机构;扭力监测
摘要：
汽车转向系统的装配是汽车零部件装配过程中的一个重要环节,也是汽车安全性能的保障。而转向横拉杆是汽车转向系统中的重要零件,它影响着汽车操纵的稳定性、行驶的安全性、以及轮胎的使用寿命。针对横拉杆自动装配过程中齿条的对中保障、左右横拉杆安装受力均匀的需求,本文提出基于PLC的汽车横拉杆拧紧系统。首先利用标准件对拧紧系统的工装进行对中校验,以确保系统使用时稳定可靠,从而保障横拉杆的抗拉强度。其次,通过定位及检测装置对齿条进行夹紧固定,保障齿条处在夹具中心位置。最后采用伺服机构高精度定位拧紧机的工作位置,通过多轴拧紧控制器控制左右拧紧机同步拧紧,从而实现左右横拉杆安装过程中受力均匀。本文提出的汽车横拉杆拧紧系统已应用于某公司的电子转向系统自动装配线,通过测试表明,该系统能实现左右横拉杆的安装过程受力均匀。
语种：
中文
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A fast detection and grasping method for mobile manipulator based on improved faster R-CNN
作者：
Zhang, Hui* ;Tan, Jinwen;Zhao, Chenyang;Liang, Zhicong;Liu, Li;...
期刊：
Industrial Robot ,2020年47(2):167-175 ISSN：0143-991X
通讯作者：
Zhang, Hui
作者机构：
[Zhang, Hui; Liang, Zhicong; Tan, Jinwen; Fan, Shaosheng; Zhao, Chenyang] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha, Peoples R China.;[Liu, Li; Zhong, Hang] Hunan Univ, Changsha, Peoples R China.
通讯机构：
[Zhang, Hui] C;Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha, Peoples R China.
关键词：
Grippers;Robotics;Machine vision;Robot vision;Automated guided vehicles (AGV);Improved faster R-CNN;DACAB;Object detection;Mobile manipulator
摘要：
Purpose: This paper aims to solve the problem between detection efficiency and performance in grasp commodities rapidly. A fast detection and grasping method based on improved faster R-CNN is purposed and applied to the mobile manipulator to grab commodities on the shelf. Design/methodology/approach: To reduce the time cost of algorithm, a new structure of neural network based on faster R CNN is designed. To select the anchor box reasonably according to the data set, the data set-adaptive algorithm for choosing anchor box is presented; multiple models of ten types of daily objects are trained for the validation of the improved faster R-CNN. The proposed algorithm is deployed to the self-developed mobile manipulator, and three experiments are designed to evaluate the proposed method. Findings: The result indicates that the proposed method is successfully performed on the mobile manipulator; it not only accomplishes the detection effectively but also grasps the objects on the shelf successfully. Originality/value: The proposed method can improve the efficiency of faster R-CNN, maintain excellent performance, meet the requirement of real-time detection, and the self-developed mobile manipulator can accomplish the task of grasping objects. © 2020, Emerald Publishing Limited.
语种：
英文
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医药输液灯检机对产品异物准确检测仿真
作者：
张辉;李宣伦
期刊：
计算机仿真 ,2019年36(2):330-335 ISSN：1006-9348
作者机构：
长沙理工大学电气与信息工程学院,湖南长沙410004;湖南大学机器人视觉感知与控制技术国家工程实验室 湖南长沙410082;长沙理工大学电气与信息工程学院,湖南长沙,410004;[李宣伦] 长沙理工大学;[张辉] 湖南大学
关键词：
异物检测;分块主成分追踪;稀疏矩阵分块聚类;轨迹空间特征向量;分层联合稀疏表示
摘要：
针对250 mL及以上医药大输液生产过程中造成药液中出现毛发、漂浮物、玻璃屑等可见异物的在线实时检测难题,开发了一种基于分层联合稀疏表示的医药输液全自动智能灯检机。首先通过改进的分块主成分追踪算法对序列图像中的运动目标进行检测以排除静止背景噪声干扰,然后利用稀疏矩阵分块聚类算法得到运动目标的运动轨迹并提取运动轨迹的空间特征向量,最后为了提高传统稀疏表示分类器对异物识别的能力,提出分层联合稀疏表示分类器根据运动轨迹的空间特征向量对异物进行识别,以排除随机噪声的干扰。仿真结果证明,该系统克服了检测过程中各种噪声干扰对异物识别的影响,解决了医药大输液可见异物的在线实时检测难题。
语种：
中文
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Automated Visual Inspection of Glass Bottle Bottom with Saliency Detection and Template Matching
作者：
Zhou, Xianen;Wang, Yaonan;Xiao, Changyan* ;Zhu, Qing* ;Lu, Xiao;...
期刊：
IEEE Transactions on Instrumentation and Measurement ,2019年68(11):4253-4267 ISSN：0018-9456
通讯作者：
Xiao, Changyan;Zhu, Qing
作者机构：
[Wang, Yaonan; Zhou, Xianen; Xiao, Changyan; Zhu, Qing] Hunan Univ, Natl Engn Lab Robot Visual Percept & Control Tech, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.;[Lu, Xiao] Hunan Normal Univ, Coll Engn & Design, Changsha 410081, Hunan, Peoples R China.;[Zhang, Hui] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China.;[Ge, Ji] Univ Toronto, Adv Micro & Nanosyst Lab, Toronto, ON M5S 3G8, Canada.;[Zhao, Huihuang] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421008, Peoples R China.
通讯机构：
[Xiao, CY; Zhu, Q] H;Hunan Univ, Natl Engn Lab Robot Visual Percept & Control Tech, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.
关键词：
Inspection;Saliency detection;Cameras;Visualization;Glass;Defect detection;machine vision;multiscale filtering;saliency detection;template matching
摘要：
Glass bottles are widely used as containers in the food and beverage industry, especially for beer and carbonated beverages. As the key part of a glass bottle, the bottle bottom and its quality are closely related to product safety. Therefore, the bottle bottom must be inspected before the bottle is used for packaging. In this paper, an apparatus based on machine vision is designed for real-time bottle bottom inspection, and a framework for the defect detection mainly using saliency detection and template matching is presented. Following a brief description of the apparatus, our emphasis is on the image analysis. First, we locate the bottom by combining Hough circle detection with the size prior, and we divide the region of interest into three measurement regions: central panel region, annular panel region, and annular texture region. Then, a saliency detection method is proposed for finding defective areas inside the central panel region. A multiscale filtering method is adopted to search for defects in the annular panel region. For the annular texture region, we combine template matching with multiscale filtering to detect defects. Finally, the defect detection results of the three measurement regions are fused to distinguish the quality of the tested bottle bottom. The proposed defect detection framework is evaluated on bottle bottom images acquired by our designed apparatus. The experimental results demonstrate that the proposed methods achieve the best performance in comparison with many conventional methods.
语种：
英文
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Distributed Multi-Robot Formation Control Based on Two-Layer Nearest Neighbor Information(TNNI) Consensus
作者：
Deng, Guang* ;Zhang, Hui;Zhong, Hang;Miao, Zhiqiang;Liu, Li;...
作者机构：
[Zhang, Hui; Deng, Guang] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha, Hunan, Peoples R China.;[Liu, Li; Yu, Miao; Zhong, Hang; Miao, Zhiqiang] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China.;[Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON, Canada.
会议名称：
IEEE International Conference on Systems, Man and Cybernetics (SMC)
会议时间：
OCT 06-09, 2019
会议地点：
Bari, ITALY
会议主办单位：
[Deng, Guang;Zhang, Hui] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha, Hunan, Peoples R China.^[Zhong, Hang;Miao, Zhiqiang;Liu, Li;Yu, Miao] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China.^[Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON, Canada.
会议论文集名称：
IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
摘要：
With the development of artificial intelligence, robot swarm systems also frequently appear in complex tasks of different situation. One of the important research directions is the formation of multi-robots. This paper analyzes the limitations of existing algorithms for large-scale mobile robot swarm formation control problems and proposes a consensus control algorithm with two-layer nearest neighbor information. It carries out experimental simulation to verify its convergence performance. At the same time, combined with a distributed structure control strategy that can change the number of robot formation members, the formation control experiment is carried out on the experimental platform consisted of robot state information detection device and multiple mobile robots, to further verify its feasibility. © 2019 IEEE.
语种：
英文
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Circumnavigation of a Moving Target in 3D by Multi-agent Systems with Collision Avoidance: An Orthogonal Vector Fields-based Approach
作者：
Zhong, Hang;Wang, Yaonan;Miao, Zhiqiang* ;Tan, Jianhao;Li, Ling;...
期刊：
International Journal of Control, Automation and Systems ,2019年17(1):212-224 ISSN：1598-6446
通讯作者：
Miao, Zhiqiang
作者机构：
[Zhong, Hang; Miao, Zhiqiang; Wang, Yaonan; Tan, Jianhao] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.;[Zhang, Hui; Li, Ling] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China.;[Fierro, Rafael] Univ New Mexico, Dept Elect & Comp Engn, MARHES Lab, Albuquerque, NM 87131 USA.
通讯机构：
[Miao, Zhiqiang] H;Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.
关键词：
Circumnavigation;collision avoidance;multi-agent systems;potential function;target tracking/enclosing;vector fields
摘要：
The problem of circumnavigating a moving target in a three dimensional setting by a network of agents while avoiding inter-agent collisions is addressed in this paper. A distributed control strategy is proposed for the multi-agent system to achieve three objectives: reaching the target plane with predesigned orientation, circulating around the target with prescribed radius, and avoiding collisions among agents. After representing the control objectives by three potential functions, the gradient fields of which are orthogonal to each other, the control law then is developed using the gradient vector field-based approach. The novelty of the proposed controller lies in the orthogonality of the vector fields, which decouples the control objectives and ensures global asymptotic convergence to the desired motion, subject to some mild initial condition constraints. The stability and convergence analysis are presented using Lyapunov tools, and the effectiveness of the proposed control strategy is demonstrated through numerical simulations.
语种：
英文
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基于改进RRT的路径规划算法
作者：
刘晓倩;张辉;王英健
期刊：
自动化技术与应用 ,2019年38(5):96-100 ISSN：1003-7241
作者机构：
长沙理工大学电气与信息学院,湖南长沙,410114;[刘晓倩; 张辉; 王英健] 长沙理工大学
关键词：
路径规划;目标偏向采样策略;贪心思想
摘要：
传统的RRT(Rapid-exploration Random Tree)算法具有搜索速度快,适用于解决动力学非完整性约束问题,但是由于算法本身的随机性,生成的路径比较曲折,甚至出现绕远路现象.为此,本文提出一种改进的RRT路径规划算法,该算法结合目标偏向策略,使算法快速向目标节点收敛;对选取节点的度量函数,加入了角度的影响;同时引入贪心剪枝思想,对冗余节点进行剪枝,提高了路径规划算法的效率;最后通过仿真实验,验证了该算法的正确性和有效性.
语种：
中文
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Automatic Kidney Lesion Detection for CT Images Using Morphological Cascade Convolutional Neural Networks
作者：
Zhang, Hui* ;Chen, Yurong* ;Song, Yanan;Xiong, Zhenlin;Yang, Yimin;...
期刊：
IEEE ACCESS ,2019年7:83001-83011 ISSN：2169-3536
通讯作者：
Zhang, Hui;Chen, Yurong
作者机构：
[Zhang, Hui; Song, Yanan; Xiong, Zhenlin; Chen, Yurong; Zhang, H] Changsha Univ Sci & Technol, Dept Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China.;[Yang, Yimin] Lakehead Univ, Comp Sci Dept, Thunder Bay Campus, Thunder Bay, ON P7B 5E1, Canada.;[Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada.
通讯机构：
[Zhang, H; Chen, YR] C;Changsha Univ Sci & Technol, Dept Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China.
关键词：
deep learning;Kidney lesion detect;morphology;RCNN
摘要：
The CT scan image is one of the most useful tools for diagnosing and locating lesions in the kidney. It can provide precise information about the location and size of lesions in many medical applications. Manual and traditional medical testings are labor-consuming and time-costing. Nowadays, detecting lesions in CT automatically is an integral assignment to the paramount importance of clinical diagnosis. Computer-aided diagnosis (CAD) is needed to develop and improve medical testing efficiency. However, it is still a tremendous challenge to the extant low precision and incomplete detection algorithm. In this paper, we proposed a lesion detection tool using multi intersection over union (IOU) threshold based on morphological cascade convolutional neural networks (CNNs). For improving the detection of small lesions (1-5 mm) and increasing the stableness of network, we proposed two morphology convolution layers and modified feature pyramid networks (FPNs) in the faster RCNN and combined four IOU threshold cascade RCNNs. In this lesion detection task, the modified CNN was trained in pytorch framework. The experiments were conducted in CT kidney images of DeepLesion that are published by hospitals' picture archiving and communication systems (PACSs). Finally, our method achieved AP of 0.840 and AUC of 0.871, and the results demonstrated that our proposed detector is an outstanding tool for detecting lesions in CT and outperformed in the data set. © 2019 IEEE.
语种：
英文
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基于贝叶斯CNN和注意力网络的钢轨表面缺陷检测系统
作者：
金侠挺;王耀南;张辉;刘理;钟杭;...
期刊：
自动化学报 ,2019年45(12):2312-2327 ISSN：0254-4156
作者机构：
湖南大学电气与信息工程学院 长沙 410082;湖南大学机器人视觉感知与控制技术国家工程实验室 长沙 410082;长沙理工大学电气与信息工程学院 长沙 410114;郑州轻工业大学电气与信息工程学院 郑州 450000;[钟杭; 刘理; 金侠挺; 王耀南; 张辉] 湖南大学
关键词：
钢轨表面缺陷;视觉检测;贝叶斯卷积神经网络;注意力机制;类别不平衡
摘要：
面向复杂多样的钢轨场景,本文扩展了最先进的深度学习语义分割框架DeepLab v3+到一个新的轻量级、可伸缩性的贝叶斯版本DeeperLab,实现表面缺陷的概率分割.具体地, Dropout被融入改进的Xception网络,使得从后验分布中生成蒙特卡罗样本;其次,提出多尺度多速率的空洞空间金字塔池化(Atrous spatial pyramid pooling, ASPP)模块,提取任意分辨率下的密集特征图谱;更简单有效的解码器细化目标的边界,计算Softmax概率的均值和方差作为分割预测和不确定性.为解决类别不平衡问题,基于在线前景 –背景挖掘思想,提出损失注意力网络(Loss attention network, LAN)定位缺陷以计算惩罚系数,从而补偿和抑制DeeperLab的前景与背景损失,实现辅助监督训练.实验结果表明本文算法具有91.46 %分割精度和0.18 s/帧的运行速度,相比其他方法更加快速鲁棒.
语种：
中文
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桥梁检测机器人作业规划与位姿优化方法研究
作者：
刘理;王耀南;张辉;万智;贾林
期刊：
仪器仪表学报 ,2019年40(7):147-158 ISSN：0254-3087
通讯作者：
Liu, L.
作者机构：
湖南大学电气与信息工程学院机器人视觉感知与控制技术国家工程实验室;长沙理工大学电气与信息工程学院;[万智] 湖南桥康智能科技有限公司;[刘理; 王耀南; 贾林] 湖南大学;[张辉] 长沙理工大学
通讯机构：
National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering, Hunan University, Changsha, China
关键词：
桥梁检测机器人;作业规划;位姿优化;不等式约束优化
摘要：
针对桥梁底部病害人工检测的作业难题,介绍了桥梁检测机器人的工作原理,结合桥梁的结构化特征和视觉检测拍摄参数约束,研究了桥梁检测机器人作业规划与位姿优化方法。首先,提出一种以最佳拍摄模型约束的桥梁检测机器人拍摄作业位姿规划方法。在最佳拍摄规划方法的基础上,针对小箱梁桥梁和T型梁桥梁底部的褶皱结构,研究了以安全拍摄模型为约束的拍摄位姿优化方法,设计了结合拍摄偏角和拍摄距离的权重函数,推导了优化算法公式并给出了收敛证明。通过对不同拍摄参数的配置,进行了针对空心板桥梁的拍摄作业位姿规划方法仿真;针对小箱梁桥梁的结构,在位姿规划仿真结果基础上进行了位姿优化方法的仿真。最后以研制的桥梁检测机器人为对象,进行了现场测试与验证,仿真和实验结果均表明,该规划和优化方法符合桥梁拍摄检测的要求,具有很好的鲁棒性和实时性。
语种：
中文
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