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High Precision Tuning Device of Microwave Cavity Filter Based on Hand-eye Coordination

High Precision Tuning Device of Microwave Cavity Filter Base...

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第三十八届中国控制会议

作者： Chaolong Yao Yan Yuan Jie Li Leyu Bi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Based on the structure and dynamic tuning characteristics of the microwave cavity filter, the method of vision assisting mechanical arm motion is used for tuning. In order to meet the flexibility and high precision requirements of the microwave cavity filter tuning system, the thesis improves image recognition and hand-eye coordination methods. Image recognition using Otsu method for image segmentation, the relative 3 d position coordinates of the target screw are obtained by edge fitting circle and image sharpness, and the screw angle was extracted by dynamically obtaining the screw groove thread area, which was used to improve the applicability and accuracy of screw positioning and thread angle extraction. The hand-eye coordination part proposes a hand-eye coordination method based on image feedback. Through the feedback of the image, the PID control robot arm is continuously moved to make the screw center and the image center overlap to achieve hand-eye coordination. The experimental results show that compared with the traditional hand-eye calibration method, the method takes less time and has lower hand-eye coordination error, which greatly improves the flexibility and precision of the tuning system. Based on the improved method of image recognition and hand-eye coordination, it can realize accurate and fast tuning of microwave cavity filter, and it also has certain guiding significance for the tuning of similar industrial equipment.

关键词： hand-eye coordination microwave cavity filter image positioning visual feedback

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Self-Adaptive PCNN Based on Maximum Entropy and its Application in Handwritten Digit Recognition

Self-Adaptive PCNN Based on Maximum Entropy and its Applicat...

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第三十八届中国控制会议

作者： Rui Zhu Wei-Hua Cao Zhe-Yi Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper mainly studies the self-adaptation of Pulse Coupled Neural Network(PCNN) and the application in handwritten digit recognition. First, the edge extraction algorithm of image using PCNN and maximum entropy is proposed, the parameters' optimization of PCNN is realized by Simple Genetic Algorithm. Then, the foveation algorithm based on PCNN is used to extract the feature points of handwritten digits. Finally, a BP neural network with two hidden layers is used to recognize the images of handwritten digits which have been preprocessed. Experimental results on handwritten digit recognition demonstrated that the proposed method reached good performance on feature extraction and the recognition has better accuracy compared with the original method using BP neural network directly.

关键词： PCNN self-adaptation foveation algorithm BP neural network

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Parallel Architecture Based Iterative Segmentation Optimal Cyclic Block Kernel Learning Algorithm

Parallel Architecture Based Iterative Segmentation Optimal C...

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第三十八届中国控制会议

作者： Lu Li Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The kernel learning algorithm has been widely used to solve the generalization problem existing in reinforcement learning. However, when the state-action space of the sample is large, the computation and storage burden in the kernel learning algorithm will increase. In such case, there will be long running time and the real-time performance of the control system cannot be guaranteed. Therefore, in order to enhance the computational speed, this paper proposes a parallel architecture based iterative segmentation optimal cyclic block kernel learning algorithm. The experimental results show that the proposed method can significantly improve the computational efficiency of the kernel learning algorithm, which has important engineering practice significance.

关键词： Kernel Learning Algorithm Iterative Segmentation Cyclic Block Parallel Architecture

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Extraction of Color Characteristics of Pesticide Detection Card Based on Machine Vision

Extraction of Color Characteristics of Pesticide Detection C...

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第三十八届中国控制会议

作者： fang Jin xin Tu kaifeng Dong junlei Song wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, aiming at the pesticide residue in water resources, considering the necessity of rapid detection on site,a method based on machine vision for pesticide residue detection is proposed. The method combines machine vision and image processing technology to quickly extract the RGB three-component eigenvalues of the pesticide residue detection card. Each RGB channel has 256 brightness levels, which can overcome the shortcomings of low brightness level and indistinct image,and improve the accuracy of detection. The results show that the method is simple,fast and efficient, it is suitable for quickly extracting the characteristic values of pesticide residue detection cards.

关键词： Machine vision pesticide residue detection RGB color space

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Multi-Features Fusion Based on Boolean Map for Video Saliency Detection

Multi-Features Fusion Based on Boolean Map for Video Salienc...

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第三十八届中国控制会议

作者： Longsheng Wei Min Wang Wei Liu Xinmei Wang Jiale Sun Xu Yin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Video saliency detection aims to extract salient objects in video. In order to resolve the problems of incomplete extraction salient area and the mixing between background and salient objects at boundary, this paper proposes a video saliency detection method via multi-features fusion based on Boolean Map. The main innovation in this method is that global topological relationship of video frames are utilized to compute saliency values. Firstly, boolean maps are generated according to the Boolean Map theory via combine motion features and color features in videos, and then attention maps are calculated by masking unsurroundedness area, finally, video saliency maps are obtained by fusing all attention maps. Experiments on Segtrack V2 and Fukuchi benchmark datesets show that the proposed method successfully obtains complete and clear boundary salient area, and it outperforms the other general models.

关键词： Video saliency detection Boolean map Multi-features fusion

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Synchronization of a Class of Discrete-Time Nonlinear Singularly Perturbed complex Networks

Synchronization of a Class of Discrete-Time Nonlinear Singul...

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第三十八届中国控制会议

作者： Yongzhi Li Yuqing Li Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, the problem of synchronization is investigated for a class of discrete-time nonlinear singularly perturbed complex networks(SPCNs). A slow sampling discrete-time nonlinear SPCN model is first devised, which includes the slow and the fast states as well as the general sector-like nonlinear functions. By utilizing the Kronecker product, a new Lyapunov function dependent on singular perturbation parameter(SPP) is constructed. A sufficient condition in terms of linear matrix inequalities(LMIs) is derived under which the discrete-time nonlinear SPCN is globally asymptotically synchronized. When these LMIs have feasible solutions, the global asymptotic synchronization is ensured and the upper bound of the SPP is evaluated. A numerical example is given to illustrate the effectiveness of our results.

关键词： complex networks Synchronization Singularly perturbed systems Discrete-time systems

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Anti-Occlusion Correlation Filter Tracking Based on Multi-Peaks Response

Anti-Occlusion Correlation Filter Tracking Based on Multi-Pe...

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第三十八届中国控制会议

作者： Jiale Sun Longsheng Wei Wei Liu Feng Liu Min Wang Xu Yin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Aiming at the problem that the target occlusion and target loss in the target tracking process can not be solved by most tracking algorithms, anti-occlusion correlation filter tracking based on multi-peaks response is proposed. When the target is occluded, the response of the multi-peaks and the highest peaks exceeds the set thresholds, and the two-dimensional matrix of the Gaussian distribution is used to perform a point multiplication operation with the confidence map to obtain a new confidence map, and the current frame model update is stopped. Experiments show that compared with other algorithms, the algorithm has a significant improvement in tracking accuracy and speed when dealing with video sequences whose targets are occluded.

关键词： Visual tracking Correlation filter Occlusion Multi-peaks response

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Spectral Reflectance Reconstruction Based on Spectral Optimization of Light Source

Spectral Reflectance Reconstruction Based on Spectral Optimi...

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第三十八届中国控制会议

作者： Hui Jiang Xin Wang Jing-Jing Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

As a unique property of the object surface, the spectral reflectance plays an important role in computer vision applications and in realistic material reproduction. To determine the influence of the light source on the spectral reflectance reconstruction accuracy, the pseudo-inverse method is adopted to reconstruct the spectral reflectance. Further, the genetic algorithm is used to optimize the light source for improving the reconstruction accuracy. The experiment results show that the spectral reflectance reconstruction accuracy is highly affected by the light source spectra, and the light source spectra optimized by the proposed strategy significantly outperforms several commonly used illumination source.

关键词： Spectral Reflectance Reconstruction Genetic Algorithm Pseudo Inverse Operation

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Design of Surface Magneto-Optical Kerr Effect Automatic Measurement System Based on LabVIEW

Design of Surface Magneto-Optical Kerr Effect Automatic Meas...

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第三十八届中国控制会议

作者： Laizhe Zhu Kaifeng Dong Fang Jin Junlei Song Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

It is of great significance for accurate and fast magnetic measurement of high magneto-crystalline anisotropy film materials. In this paper, an surface magneto-optical Kerr effect automatic measurement system based on LabVIEW is designed according to the practical requirements of hysteresis loop measurement of magnetic films. The system takes the SR830 lock-in amplifier as core, combined with virtual instrument technology and correlative detection technology, which achieves the effective measurement of the weak Kerr signal of Ni Fe soft magnetic film material under strong noise environment, and automatically draws its hysteresis loop. The measurement system has high resolution, high output signal-to-noise ratio, high automation, and has good application value.

关键词： SMOKE hysteresis loop virtual instrument LabVIEW lock-in amplifier

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Restore the Incomplete Calligraphy Based on Style Transfer

Restore the Incomplete Calligraphy Based on Style Transfer

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第三十八届中国控制会议

作者： Mengxi Qin Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Calligraphy is an important humanistic symbol of Chinese civilization. However, most of the calligraphy is incomplete, which has only a small number of Chinese characters circulating in the world. How to use these samples to efficiently restore the remaining calligraphy characters has always been considered as a difficult task. In this work, we propose Densenetpix2 pix model based style transfer method to solve this problem. By training some samples to learn the rules of transferring the printed font images to the calligraphy characters images, Densenet-pix2 pix can predict the remaining calligraphy characters. Our method modify the generation network and optimization strategies of style transfer, which improves the generation quality of the calligraphy characters and the stability of the model. In addition, we use pre-trained feature extraction models to extract content information and style information, and scientifically evaluate the quality of our generated calligraphy characters from these two aspects. We compared our method with several other baseline methods. The experimental results show that our method can effectively restore the remaining calligraphy characters, and the generated Chinese characters are more delicate.

关键词： Calligraphy characters Style transfer Restore Generation

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