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作者： Fan Yang Zhi Liu School of Electrical and Information Engineering Wuhan University of Technology Hubei Provincial Video Image and HD Projection Engineering Technology Research Center

The wireless sensor network is an important part of the Internet of Things system. It has many features, short life, and is not easy to replace. The aggregation node is experiencing more data transmission tasks and the energy is exhausted faster, which makes the system paralyzed. In response to this problem, this paper introduces a new mobile aggregation node, and specifically plans its mobile strategy, which can better complete the aggregation of the underlying static node data, so that the system not only has better computing and storage capabilities, but also It is not subject to energy loss, which effectively improves the service life of the system.

关键词： wireless sensor network mobile aggregation node mobility strategy

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Non-local Hessian-based weighted filter for 2D noisy angiogram image enhancement with cardiovascular tree structure preservation

Non-local Hessian-based weighted filter for 2D noisy angiogr...

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Chinese Automation Congress

作者： Zhenghua Huang Qian Li Hanyu Hong Tianxu Zhang Nong Sang Hubei Engineering Research Center of Video Image and HD Projection Wuhan Institute of Technology Wuhan Hubei China Huazhong University of Science and Technology Wuhan Hubei China

The Hessian-based filter had been already proven to be an effective method for enhancing vessels in 2D angiographic images. However, conventional Hessian-based filters are usually sensitive to noise and cannot preserve vascular structure very well. In this paper, a novel Hessian-based filter is proposed for enhancing 2D noisy angiography images. The proposed approach firstly incorporates a non-local operator in the Hessian matrix to obtain noiseless eigenvalues in a noisy environment, and then the relation of local image is carried by an exponent function which is used to suppress non-vascular structure around real vascular structure. Both qualitative and quantitative results of simulated experiments demonstrate that such approach is far superior to other two Hessian-based approaches in denoising, suppressing non-vascular areas, and enhancing vascular structure. Simultaneously, the results of extensive experiments on clinical X-ray angiography images further verify that our method performs better than the other two ones on obtaining high-quality enhanced vascular images which are beneficial for applications such as vessel segment, vessel motion analysis, and three-dementional reconstruction of vessel tree.

关键词： Non-local hessian-based filter image enhancement Structure preservation X-ray angiogram image

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Realization of Detection Algorithms for Key Parts of Unmanned Aerial Vehicle Based on Deep Learning

Realization of Detection Algorithms for Key Parts of Unmanne...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Guangya Wang Hanyu Hong Yaozong Zhang Jinmeng Wu Yunfei Wang Shiyang Li Hubei Key Laboratory of Optical Information and Pattern Recognition School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China Hubei Engineering Research Center of Video Image and HD Projection

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

Fixed-point attack on the key parts of small aerial vehicles is one of the important means of UAV (Unmanned Aerial Vehicle) countermeasure. Fixed-wing aircraft flying in the air has two characteristics: fast speed and fast attitude change of aircraft. However, the traditional detection method of key parts of fixed-wing aircraft in infrared images is not only slow in speed but also low in accuracy. This paper presents an improved target detection and motion tracking algorithm based on deep learning method. The algorithm uses a deeper neural network to enhance the feature extraction capabilities of CNN and obtain richer feature information. The detection algorithm obtains the position and motion direction of the key points of the target. Experimental results show that the detection algorithm proposed in this paper is up to 30 frame/s, with an average accuracy of 91.5%/. The method achieved good results in the experiment.

关键词： Feature extraction Aircraft Unmanned aerial vehicles Convolution Target recognition Prediction algorithms Object detection

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Automatic Docking Design of Flange Pipe Based on Spatial Information

Automatic Docking Design of Flange Pipe Based on Spatial Inf...

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International Conference on Information Science and Control engineering (ICISCE)

作者： Xingxun Li Xiuhua Zhang Jinmeng Wu Jian Huang Pianpian Chen Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Wuhan China Hubei Engineering Research Center of Video Image and HD Projection Wuhan Institute of Technology Wuhan China

With the development of ship industry, pipeline system has been more and more widely used. However, the pipeline site space is narrow. Mechanical and electrical equipments are of all kinds. The pipeline cable is densely distributed. All problems mentioned above seriously affects the pipeline construction. In order to solve the problem of pipeline docking, the method of making model and comprehensive lofting is usually adopted. However, this method is technically backward. The operation is inconvenient due to the narrow onsite space. The required period is long. With low information utilization and accuracy, the method of making model and comprehensive lofting has a great influence on the development cycle and design quality. In order to solve these problems, this paper presents a design method and system of flange pipe docking. A binocular camera is used to obtain the image of the pipe joint. The center position of the flange surface and array holes on the flange surface are extracted from the image, which is bias of subsequent work. First, the path of the intermediate connecting pipe is calculated. Then, according to the pipe standards of intermediate connection pipe and production specification of enterprise, the model of intermediate connecting pipe is automatically generated by using secondary development technology of CAD. In this paper, the binocular vision technology is combined with pipeline docking design, which significantly improves the utilization rate of field space information and design efficiency, and solves the problems of inconvenient operation and safety risk of traditional profiling method.

关键词： Industries Solid modeling Design methodology Pipelines Production Flanges Feature extraction

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Identification and Extraction of Circular Markers in 3D Reconstruction

Identification and Extraction of Circular Markers in 3D Reco...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Yunfei Wang Hanyu Hong Jinmeng Wu Guangya Wang Shiyang Li Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan China Hubei Engineering Research Center of Video Image and HD Projection Wuhan China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

This paper presents a method for the identification and location of circular markers in 3D reconstruction. The input image is processed with gray scale and gaussian filter to remove noise interference and improve the accuracy of edge detection. The size and direction of the gradient of the image were calculated to obtain the edge features of the circular marker, and the circle degree of the closed edge was judged, and the center of the marker was obtained by fitting the edge features with the ellipse of the least square method. Hu moment similarity of each marker was obtained, and the non-marker was deleted and the real marker was retained by similarity judgment. Experiments show that the algorithm has good robustness, high precision, can effectively reduce the probability of false detection, and has high accuracy in complex environments.

关键词： image edge detection Transforms Three-dimensional displays Fitting Feature extraction Cameras Least mean squares methods

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The Intelligent Preparation of Scene Matching Guidance Reference Map Based on Prior Knowledge

The Intelligent Preparation of Scene Matching Guidance Refer...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Pan Chen Yaozong Zhang Jinmeng Wu Xingxun Li School of Electrical Information Wuhan Institute of Technology Wuhan China Hubei Engineering Research Center of Video Image and HD Projection Wuhan China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

Aiming at the problem that the automatic processing level of reference map preparation in image matching guidance is not high enough, our work proposes a novel reference map preparation based on the prior knowledge such as infrared imaging conditions and trajectory information. In the image preprocessing stage, the deep convolution network is used to extract the regions of interest automatically and meanwhile, combined with the analysis of connected region, the ROI extraction results can be optimized; Then, the natural scene is classified by texture of material, and the periodic temperature change of the feature is automatically mapped to the gray level, which conforms to the actual imaging characteristics and reduces the artificial gray level error. Next, combined with trajectory information and perspective transformation, multi-scale and multi-view scene images can be automatically obtained, which can avoid the situation that the manually selected target or landmark is not obvious or does not exist in the actual imaging. With comprehensive analysis from three aspects of reliability, stability and uniqueness, the best matching area is automatically determined, which improves the accuracy of matching algorithm and the time performance of reference map preparation system.

关键词： Temperature Convolution Target recognition Real-time systems Surface treatment Knowledge engineering Atmospheric modeling

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A Progressive Focus Feature Extraction Based Multi-Focus image Fusion Via Lbp and Local Lacunarity Metric

SSRN

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SSRN 2024年

作者： Zhang, Xiuhua Peng, Cong Dong, Chenpeng Ma, Yiran Liuc, Xiaohua School of Mechanical and Electrical Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Provincial Video Image and HD Projection Engineering Technology Research Center Wuhan Institute of Technology Wuhan430205 China School of Computer Science & Engineering Artificial Intelligence Wuhan Institute of Technology Wuhan430205 China

Multi-focus image fusion is prone to problems such as loss of image details, block effects, and edge artifacts, which seriously affect the quality of image fusion. In this paper, we propose a progressive focus feature extraction (PFFE) based multi-focus image fusion approach. Firstly, local binary pattern (LBP) is used to extract the texture focus features of multi-focus images, then the local lacunarity metric (LLM) is utilized to estimate the structure focus features. Secondly, guided filter is used to enhance the focus features, and Wasserstein distance is regarded as a metric for adaptive window size selection. Finally, the decision map based on extreme value strategy and progressive focus features is combined with weighted mapping to obtain the fusion result. The experimental results show that our method outperforms the state-of-the-art methods in both subjective and objective evaluations, and can increase image feature metric (Qm) by 292% and reduce the mean square error (MSE) by 34%. © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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All-Weather Real-Time Ore Detection Method Based on Near-Infrared Structured Light and Zero-Crossing Points Characteristics

SSRN

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SSRN 2023年

作者： Tian, Keyun Hong, Hanyu Zhang, Xiuhua Peng, Cong Wu, Yuanzhe Zhu, Cheng Hubei Provincial Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Wuhan430205 China Hubei Provincial Video Image and HD Projection Engineering Technology Research Center Wuhan Institute of Technology Wuhan430205 China School of Electrical Information Wuhan Institute of Technology Wuhan430205 China School of Mechanical and Electrical Engineering Wuhan Institute of Technology Wuhan430205 China

To address the low efficiency of ore detection methods caused by the complex lighting environment of mining sites, an all-weather real-time ore detection method based on near-infrared structured light and zero-crossing points characteristics was proposed. Firstly, an image acquisition method based on the physical model of infrared radiation is proposed to avoid structured light imaging being disturbed by a strong sunlight environment;Then, the centerline of the light bar is extracted quickly and accurately based on the zero-crossing point characteristics;Finally, the light bar neighborhood splicing detection method was proposed to realize the real-time detection and 3D measurement of the target ore. The experimental results show that the proposed method can effectively resist strong sunlight interference and faster detection speed, the average extraction time of light bar centerline per frame is below 1.8ms, and the error rate of ore size detection is less than 5%. © 2023, The Authors. All rights reserved.

关键词： Infrared radiation

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