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2009中国控制与决策会议

作者： WU Cheng-dong,WANG Li,ZHANG Yun-zhou,CHU Hao College of Information Science & Engineering,Northeastern University,Liaoning,Shenyang,China 110004

＜正＞A novel license plate positioning algorithm is proposed in this *** algorithm is composed of two parts, which are candidate region position and pseudo-region *** the texture features are used to find candidate plates *** a sliding strip window,which scans image from top to bottom,is used to select connectivity regions in the binary image of the candidate *** pseudo-plate regions are removed from the candidate plates by using plate syntactic *** plates in complex scene and fuzzy image both can be solved ***,the proposed algorithm can provide priori knowledge for next segmentation and recognition *** results show that the location method is fast and has high accuracy and strong anti-interference ability for the complex scenes and the fuzzy image particularly.

关键词： license plate position pseudo-region connectivity block plate syntax complex scene

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Research on Motion Target Detection and Tracking Algorithm Based on complex scene

Research on Motion Target Detection and Tracking Algorithm B...

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第37届中国控制会议

作者： Jin Xue-lian Yang Jian-hua Lu Wei Faculty of Electronic Information and Electrical Engineering Dalian University of Technology

In order to solve the problem of abnormal video monitoring in coal seam gas mining field,a moving target detection and tracking algorithm based on complex scene is *** this method,a segmentation algorithm based on three-frame difference method is used to divide the image into a static background region and a dynamic background region that includes the reciprocating motion of the water *** the static background area,the three-frame difference method and the background subtraction algorithm are used to merge the segmentation foreground,and the three-frame difference method is used to segment the foreground for the dynamic background area,and the foreground target is tracked by using the Kalman tracking *** show that the algorithm can accurately detect the moving target and track it in the CBM mining scene to meet the real-time requirements of video monitoring.

关键词： coal seam gas mining complex scene three-frame difference method background subtraction algorithm Kalman tracking algorithm

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Research on infrared dim and small target detection algorithm based on low-rank tensor recovery

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Journal of Systems Engineering and Electronics 2023年第4期34卷 861-872页

作者： LIU Chuntong WANG Hao College of Missile Engineering Rocket Force University of EngineeringXi’an 710025China Beijing Institute of Remote Sensing Equipment Beijing 100854China

In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detection algorithm of infrared small and dim target is proposed in this ***,the original infrared images are changed into a new infrared patch tensor mode through data ***,the infrared small and dim target detection problems are converted to low-rank tensor recovery problems based on tensor nuclear norm in accordance with patch tensor characteristics,and inverse variance weighted entropy is defined for self-adaptive adjustment of ***,the low-rank tensor recovery problem with noise is solved by alternating the direction method to obtain the sparse target image,and the final small target is worked out by a simple partitioning *** test results in various spacebased downward-looking complex scenes show that such method can restrain complex background well by virtue of rapid arithmetic speed with high detection probability and low false alarm *** is a kind of infrared small and dim target detection method with good performance.

关键词： complex scene infrared block tensor tensor kernel norm low-rank tensor restoration weighted inverse entropy alternating direction method

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Object Tracking Algorithm Based on Multi-Time-Space Perception and Instance-Specific Proposals

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Intelligent Automation & Soft Computing 2023年第7期37卷 655-675页

作者： Jinping Sun Dan Li Honglin Cheng School of Information Engineering(School of Big Data) Xuzhou University of TechnologyXuzhou221018China

Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion,a tracking algorithm based on multi-time-space perception and instance-specific proposals is proposed to optimize the mathematical model of the correlation filter(CF).Firstly,according to the consistency of the changes between the object frames and the filter frames,the mask matrix is introduced into the objective function of the filter,so as to extract the spatio-temporal information of the object with background ***,the object function of multi-feature fusion is constructed for the object location,which is optimized by the Lagrange method and solved by closed *** the process of filter optimization,the constraints term of time-space perception is designed to enhance the learning ability of the CF to optimize the final track-ing ***,when the tracking results fluctuate,the boundary suppres-sion factor is introduced into the instance-specific proposals to reduce the risk of model drift *** accuracy and success rate of the proposed algorithm are verified by simulation analysis on two popular benchmarks,the object tracking benchmark 2015(OTB2015)and the temple color 128(TC-128).Extensive experimental results illustrate that the optimized appearance model of the proposed algorithm is *** distance precision rate and overlap success rate of the proposed algorithm are 0.756 and 0.656 on the OTB2015 benchmark,which are better than the results of other competing *** results of this study can solve the problem of real-time object tracking in the real traffic environment and provide a specific reference for the detection of traffic abnormalities.

关键词： complex scene instance-specific proposals correlation filter multi-time-space perception object tracking

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