Image Recognition and Tracking Algorithm Based on PID Fuzzy Control

Video surveillance system with image recognition and image tracking capabilities has a wide range of applications in the field of city protection, social security and public safety. In this paper, based on the analysis of image detection and tracking principles, image recognition and tracking algorithm based PID fuzzy control is proposed. First, the image on the basis of the gray-scale image is acquired by the video processor and the linearization processing, and then through the expansion operation of mathematical morphology the candidate region of the image recognition is taken, and then the final image region is obtained through the vertical positioning and horizontal positioning of the region Finally, through the PID control algorithm it is the image of the track. Simulation results show that the PID fuzzy control-based image recognition and tracking algorithm possesses good vehicle license plate image recognition and tracking performance and good practicability.

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Research on Carrier Tracking Algorithm of INS-Assisted TC-OFDM Receiver with Fuzzy Control

Lecture Notes in Electrical Engineering - China Satellite Navigation Conference (CSNC 2021) Proceedings ◽

10.1007/978-981-16-3146-7_41 ◽

2021 ◽

pp. 445-455

Author(s):

Guoshun Tang ◽

Fuxing Yang ◽

Zhongliang Deng ◽

Xiwen Deng ◽

Shiwen Jiang

Keyword(s):

Fuzzy Control ◽

Tracking Algorithm

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Achieving the Measurement of Tool Diameter by the Boundary Tracing Algorithm Based on Model

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.411.469 ◽

2011 ◽

Vol 411 ◽

pp. 469-473

Author(s):

Yue Shen Lai ◽

Meng Shi ◽

Jun Wei Tian ◽

Gang Cheng

Keyword(s):

Image Recognition ◽

Least Square Method ◽

Tracking Algorithm ◽

Least Square ◽

Image Measurement ◽

Boundary Tracking ◽

Tracing Algorithm ◽

Boundary Tracing ◽

Tool Diameter ◽

Tracing Method

Boundary tracing method is an important preprocessing instrument for image recognition and image measurement, but the traditional boundary tracing method exits a conflict between the veracity and the speed. In response to these problems, we propose the boundary tracking algorithm based on the model, and then obtain the tool diameter. Experiments show that the boundary tracking algorithm can achieve a good boundary track. Compared two algorithms of diameter measurements, we obtain that the least square method runs shorter, and more efficient.

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Fuzzy control of rotary cement kiln using sintering zone image recognition

The 10th International Conference on Digital Technologies 2014 ◽

10.1109/dt.2014.6868741 ◽

2014 ◽

Cited By ~ 1

Author(s):

Dmitry Yudin ◽

Valery Magergut ◽

Vasiliy Rubanov

Keyword(s):

Fuzzy Control ◽

Image Recognition ◽

Cement Kiln ◽

Rotary Cement Kiln

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The research on tracking algorithm of intelligent vehicle based on image recognition

2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) ◽

10.1109/iccwamtip.2017.8301458 ◽

2017 ◽

Cited By ~ 1

Author(s):

Xianli Li ◽

Jiawei Zhang ◽

Senhua Wang

Keyword(s):

Image Recognition ◽

Tracking Algorithm ◽

Intelligent Vehicle

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Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189048 ◽

2020 ◽

Vol 39 (4) ◽

pp. 5699-5711

Author(s):

Shirong Long ◽

Xuekong Zhao

Keyword(s):

Feature Extraction ◽

Particle Swarm Optimization ◽

Deep Learning ◽

Real Time ◽

Image Recognition ◽

Particle Swarm ◽

Learning Technology ◽

Search Performance ◽

Swarm Optimization ◽

Teaching Mode

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

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