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KSLIC: K-mediods clustering based simple linear iterative clustering 1

2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Zhang, Houwang Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Simple Linear Iterative Clustering (SLIC) is one of the most excellent superpixel segmentation algorithms with the most comprehensive performance and is widely used in various scenes of production and living. As a preprocessing step in image processing, superpixel segmentation should meet various demands in real life as much as possible, but SLIC is highly sensitive to noise. In this paper, a K-mediods clustering based simple linear iterative clustering (KSLIC) is proposed, which replaces the K-means clustering in SLIC with a modified local K-mediods clustering. To evaluate the performance of KSLIC, we test it on BSD500 benchmark dataset. The results show that it outperforms SLIC in terms of different noise environments including Gaussian noise, multiplicative noise and salt and pepper noise. © Springer Nature Switzerland AG 2019.

关键词： Salt and pepper noise

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An Universal control Strategy for Planar 2-DoF Underactuated Manipulator with One Passive Joint

An Universal Control Strategy for Planar 2-DoF Underactuated...

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第40届中国控制会议

作者： Zixin Huang Yaosheng Zhou Zhen Chen Wei Wang Lejun Wang School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Innovation and Entrepreneurship Wuhan Institute of Technology School of Information and Safety Engineering Zhongnan University of Economics and Law

This paper presents an unified control strategy based on the trajectory planning and tracking control for the planar 2-Do F underactuated manipulator. The trajectory of the active link is composed of two parts. The first part trajectories are designed according to the initial and target angles of the active link. The second part trajectories are designed based on the constraints between the underactuated link and the active link. Meanwhile, the parameters of the trajectories are optimized by the differential evolution algorithm(DEA) to ensure all links eventually reach to their target values by tracking the designed trajectories. Then,the sliding mode variable structure controller are designed to make the active link track their trajectories. The effectiveness of such strategy is demonstrated through simulation results.

关键词： Planar 2-DoF underactuated manipulator Trajectory planning Tracking control Differential evolution algorithm

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Drone Image Stitching Using Local Least Square Alignment

Drone Image Stitching Using Local Least Square Alignment

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Qi Wan Linbo Luo Jun Chen Yong Wang Donghai Guo School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

This paper proposes a strategy for drone image stitching using local least square alignment, which aims to effectively stitch multiple overlapping drone images into a natural panoramic image. Existing traditional methods using simple homography cannot handle the situation that the input drone images have parallax effect, and the mosaic result always suffers from artifacts. In order to achieve natural-looking stitching results without the above limitation, we divide the proposed method into the following two steps, namely, local least square alignment and global similarity constraint. Starting from initial feature sets obtained by traditional feature extraction methods, we construct a robust alignment energy based on parallax errors to adaptively eliminate parallax effects. The energy can be efficiently minimized used least square estimate. Combined with global similarity constraint, our proposed strategy can flexibly improve the naturalness of the results. Experiments show that our stitching strategy can more effectively eliminate parallax effects and achieve natural-looking results compared to other state-of-the-art methods.

关键词： Drones Image stitching Distortion Feature extraction Optimization Geology Adaptation models

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No-Reference Image Quality Assessment using Meta-SGD

No-Reference Image Quality Assessment using Meta-SGD

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Chinese automation Congress (CAC)

作者： Qingqing Yan Bei Dong Xin Li Yiwen Xiang Dapeng Luo Longsheng Wei School of Automation China University of Geosciences Wuhan China Key Laboratory of Geological Survey and Evaluation of Ministry of Education Wuhan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Intelligent Technology co. Ltd of Chinese Construction Third Engineering Bureau Wuhan China School of Electronic Information and Mechanics China University of Geosciences Wuhan China

ISBN: (纸本)9781665426480

Deep learning-based no-reference image quality assessment (NR-IQA) algorithm requires massive training data and labels, but data scarcity usually exists in practical applications. Most of the previous metrics used pre-trained networks to solve this problem by fine-tuning on the target tasks. Unfortunately, the network trained on other tasks cannot be directly applied to IQA tasks and failed when encountering complex distortions. To reduce dependence on labeled data and improve generalization ability of unknown distortion types, a NR-IQA metric based on Meta-SGD is proposed, which can learn the quick adaptability of humans and obtain general meta-knowledge for distortion evaluation. Specifically, we collected a great many NR-IQA tasks with different distortion types to pre-train the model; then a meta-learning metric based on optimization, Meta-SGD, is proposed to acquire the meta-knowledge when evaluating images quality with various known distortions; finally, the obtained pre-trained meta-model can be directly applied to the new NR-IQA tasks only by fine-tuning a few images. Experiments on the TID2013 database demonstrate that the model after meta-learning obviously outperforms than some existing methods, and the average SRCC value for all types of distortion performance tests can reach 0.91.

关键词： Measurement Image quality Adaptation models automation Databases Training data Distortion

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Overlapped Human Pose Estimation using Non-Maximum Suppression based on Shape Similarity

Overlapped Human Pose Estimation using Non-Maximum Suppressi...

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Chinese automation Congress (CAC)

作者： Xuefu Yu Jinsheng Li Fei Xiao Wei Liu Dapeng Luo Longsheng Wei School of Automation China University of Geosciences Wuhan China Key Laboratory of Geological Survey and Evaluation of Ministry of Education Wuhan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Intelligent Technology co. Ltd of Chinese Construction Third Engineering Bureau Wuhan China School of Electronic Information and Mechanics China University of Geosciences Wuhan China

ISBN: (纸本)9781665426480

Deep Convolutional Neural Networks (DNNs) have made significant progress on human pose estimation task in recent years. However, the question of whether we are making the most use of the information we get from DNNs has not been well studied. Top-down approach which first detects person body box then utilizes single person pose estimation by heatmap is a widely used method in multi-person pose estimation. However, information that predicted by DNNs contains more information than we consider. In person box prediction process, when two persons are closed to each other, the Non-Maximum Suppression (NMS) we often use filters out the body boxes with smaller scores. For tackling this problem, we apply NMS based on Shape Similarity to person body boxes detection for tackling the problem that deleting the overlapped body boxes with smaller scores, and then extract keypoint coordinates and tag information for filter noise candidates from heatmap by Trasformer to improve the prediction accuracy. At last we develop an algorithm for refining keypoint coordinate by tag information. In experiment, we got mean Average Precision(mAP) of 76.0% in COCO2017 validation dataset, better than 75.6% with TransPose.

关键词： Heating systems Shape Pose estimation Refining Filtering algorithms Information filters Prediction algorithms

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Analysis and circuit implementation of a new fourth-order multi-wing chaotic system based on memristors

Analysis and circuit implementation of a new fourth-order mu...

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Chinese automation Congress (CAC)

作者： Lei Jia Xiaowei Jiang Xianhe Zhang Ming Chi Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Ministry of Education School of Automation China University of Geosciences Wuhan P. R. China School of Electrical Engineering and Automation Hubei Normal University Huangshi P. R. China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan P. R. China

ISBN: (纸本)9781665426480

In this paper, a new fourth-orders memristor chaotic system is obtained by introducing a smooth memristor model as the feedback term based on the modified three-orders chaotic system. The system can generate double-wing, four-wing chaos or hyperchaos for different parameters and initial conditions. Through the analysis of Lyapunov exponent and other dynamics, we can see that the system has complex chaotic, hyperchaotic, and continuous chaotic. Other dynamical behaviors such as multi-stability and extreme multi-stability are found by comparing phase and bifurcation diagrams, and equilibrium point calculations. Finally, the chaotic behavior is successfully verified by circuit simulation.

关键词： Chaos automation Circuit simulation Buildings Memristors Bifurcation Encryption

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$H_{\infty }$ PID control for Discrete-Time Fuzzy Systems With Infinite-Distributed Delays Under Round-Robin Communication Protocol

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IEEE Transactions on Fuzzy Systems 2021年第6期30卷 1875-1888页

作者： Yezheng Wang Zidong Wang Lei Zou Hongli Dong College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Department of Computer Science Brunel University London Uxbridge U.K. Institute of Complex Systems and Advanced Control and the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University Daqing China

This article is concerned with the $H_{\infty }$ proportional–integral–derivative (PID) control problem for class of discrete-time Takagi–Sugeno fuzzy systems subject to infinite-distributed time delays and round-robin (RR) protocol scheduling effects. The information exchange between the sensors and the controller is conducted through a shared communication network. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. To stabilize the target system with guaranteed $H_{\infty }$ performance index, a novel yet easy-to-implement fuzzy PID controller is developed whose integral term is calculated based on the past measurements defined in a limited time window with hope to improve computational efficiency and reduce accumulation error. Based on the Lyapunov stability theory and the convex optimization technique, sufficient conditions are derived to ensure the exponential stability as well as the $H_{\infty }$ disturbance attenuation/rejection capacity of the underlying system. Furthermore, by utilizing the cone complementarity linearization algorithm, the nonconvex controller design problem is transformed into an iterative optimization one that facilitates the controller implementation. Finally, simulation examples are given to show the effectiveness and correctness of the developed control method.

关键词： PD control Protocols PI control control systems Symmetric matrices Communication networks Optimization

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Comparison of the Smith-Waterman and Needleman-Wunsch algorithms for online similarity analysis of industrial alarm floods

Comparison of the Smith-Waterman and Needleman-Wunsch algori...

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IEEE Canada Electric Power Conference, EPEC

作者： Md Rezwan Parvez Wenkai Hu Tongwen Chen University of Alberta Edmonton Alberta Canada School of Automation and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

ISBN: (数字)9781728164892

ISBN: (纸本)9781728164908

Alarm floods are considered to be the major obstacles that prevent the smooth process operations of large-scale industrial facilities. During an alarm flood situation, industrial operators often get confused by too many alarms and thus have difficulties in observing and handling critical alarms. In recent years, sequence alignment based similarity analysis has emerged as an effective way to handle alarm floods. Alarm floods caused by the same fault are very likely to consist of the same group of alarms in a certain sequential order. Conducting realtime sequence alignment of industrial alarm floods can help operators to quickly recall the root cause and make prompt corrective actions. This paper proposes the online similarity analysis of alarm floods based on the Smith-Waterman and Needleman-Wunsch algorithms, and compares their differences and application conditions. Case studies are provided to illustrate the proposed online similarity analysis methods and the differences of the two sequence alignment algorithms.

关键词： Heuristic algorithms Indexes Prediction algorithms Power systems Pattern matching Frequency measurement Conferences

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Robotic arm calibration and teaching method based on binocular vision

Robotic arm calibration and teaching method based on binocul...

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第三十九届中国控制会议

作者： Ming Chen Xin Hong Longsheng Wei Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems CRRC Zhuzhou Locomotive Co. Ltd.

Aiming at the errors caused by the production and assembly of the robotic arm and the problem of low absolute positioning accuracy, a method of robotic arm calibration and teaching based on binocular vision is proposed in this paper. First,the joints of the robot arm is controled to rotate separately, and the motion trajectory data of the end of the robot arm is recorded by the binocular vision. Then the circle center and circle plane normal vector of each joint axis motion is optimized using Adam algorithm. After identification and calculation, accurate kinematic parameters are obtained, and then kinematically model the manipulator once again. After the calibration is completed, the user can use the teaching rod to define the trajectory under the camera, and the defined trajectory is converted to the robot arm coordinate system for inverse kinematics solution. Finally, the robotic armis controled to reproduce the trajectory. Experimental results show that the proposed method can complete the precise calibration of the kinematic parameters of the robotic arm. After calibration, the average error of the end of the robotic arm is within 1 mm, and the absolute positioning accuracy is improved by more than 80%. The method proposed in this paper has low cost and simple operation, and it is easy to be popularized and applied in industrial and desktop robotic arm calibration and teaching.

关键词： Binocular vision Calibration Kinematic modeling Teaching Positioning accuracy

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Survey on 6D Pose Estimation of Rigid Object

Survey on 6D Pose Estimation of Rigid Object

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第三十九届中国控制会议

作者： Jiale Chen Lijun Zhang Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems CRRC Zhuzhou Locomotive Co. Ltd.

Estimating 6 D pose of rigid objects has gained increasing attention as it has become an curcial problem in rapidly growing technology related to robotics, augmented reality and autonomous driving. Therefore, the research on 6 D pose estimation technology is of great significance. In this paper, firstly, current position of the field is summarized regarding object pose estimation. We found that deep learning combined with traditional methods can produce better results. Then, pose ambiguity which is an open problem needed further study is raised. Finally, the main problems of the current research and possible development directions are identified.

关键词： Pose Estimation Feature Detection Pose Ambiguity

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