Research of Image Recognition and Tracking Algorithm Based on PID Fuzzy Control

2013 ◽  
Vol 722 ◽  
pp. 472-477
Author(s):  
Wu Xue Jiang ◽  
Zhi Ming Wang ◽  
Jian Feng Luo
Keyword(s):  
Fuzzy Control ◽  
Image Recognition ◽  
Tracking Algorithm ◽  
License Plate ◽  
Image Region ◽  
Image Tracking ◽  
Detection And Tracking ◽  
Wide Range ◽  
Video Processor ◽  
Vertical Positioning

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.

scholarly journals IMPROVED BIOLOGICAL IMAGE TRACKING ALGORITHM OF ATHLETE’S CERVICAL SPINE HEALTH

2021 ◽  
Vol 27 (3) ◽  
pp. 274-277
Author(s):  
Chunmin Dai ◽  
Yang Lu
Keyword(s):  
Cervical Spine ◽  
Tracking Algorithm ◽  
Treatment Results ◽  
Level Of Evidence ◽  
Image Tracking ◽  
Detection And Tracking ◽  
Camshift Algorithm ◽  
Center Position ◽  
Feedback Algorithm ◽  
Biological Image

ABSTRACT Introduction This paper research an improved biological image tracking algorithm of athlete’s cervical spine health under color feedback. Objective A new algorithm is proposed to improve the accuracy of detection and tracking. Methods In this study, the first thing is to apply the color feedback algorithm to improve and optimize the Improved Camshift algorithm. The optimized algorithm was used to track the center of the image, and the video was processed frame by frame. The center position of the tracking frame was obtained. Results The average number of head twists per person is 39 times. Among the three groups, children twisted the least, and older adults twisted the most. Conclusion The algorithm proposed in this study has certain effectiveness and superiority and can be well applied to detecting the number of head twists during exercise. Level of evidence II; Therapeutic studies - investigation of treatment results.

Applications for a people detection and tracking algorithm using a time-of-flight camera

2014 ◽  
Vol 75 (17) ◽  
pp. 10769-10786 ◽  
Author(s):  
Carsten Stahlschmidt ◽  
Alexandros Gavriilidis ◽  
Jörg Velten ◽  
Anton Kummert
Keyword(s):  
Time Of Flight ◽  
Tracking Algorithm ◽  
People Detection ◽  
Detection And Tracking

Modelling and control of manipulators with flexible links working on land and underwater environments

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 461-470 ◽  
Author(s):  
Levent Gümüşel ◽  
Nurhan Gürsel Özmen
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Robot Manipulator ◽  
Control Methods ◽  
Control Laws ◽  
Linear Ordinary Differential Equations ◽  
Intelligent Technique ◽  
Wide Range ◽  
Classical Control ◽  
And Control

SUMMARYIn this study, modelling and control of a two-link robot manipulator whose first link is rigid and the second one is flexible is considered for both land and underwater conditions. Governing equations of the systems are derived from Hamilton's Principle and differential eigenvalue problem. A computer program is developed to solve non-linear ordinary differential equations defining the system dynamics by using Runge–Kutta algorithm. The response of the system is evaluated and compared by applying classical control methods; proportional control and proportional + derivative (PD) control and an intelligent technique; integral augmented fuzzy control method. Modelling of drag torques applied to the manipulators moving horizontally under the water is presented. The study confirmed the success of the proposed integral augmented fuzzy control laws as well as classical control methods to drive flexible robots in a wide range of working envelope without overshoot compared to the classical controls.

scholarly journals Deep Learning Based Ethiopian Car’s License Plate Detection and Recognition

2020 ◽  
Vol 8 (6) ◽  
pp. 5730-5737
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Learning Model ◽  
Motor Vehicles ◽  
License Plate ◽  
License Plate Recognition ◽  
Computer Algorithms ◽  
Wide Range ◽  
Processing Techniques ◽  
Deep Learning Model

Digital Image Processing is application of computer algorithms to process, manipulate and interpret images. As a field it is playing an increasingly important role in many aspects of people’s daily life. Even though Image Processing has accomplished a great deal on its own, nowadays researches are being conducted in using it with Deep Learning (which is part of a broader family, Machine Learning) to achieve better performance in detecting and classifying objects in an image. Car’s License Plate Recognition is one of the hottest research topics in the domain of Image Processing (Computer Vision). It is having wide range of applications since license number is the primary and mandatory identifier of motor vehicles. When it comes to license plates in Ethiopia, they have unique features like Amharic characters, differing dimensions and plate formats. Although there is a research conducted on ELPR, it was attempted using the conventional image processing techniques but never with deep learning. In this proposed research an attempt is going to be made in tackling the problem of ELPR with deep learning and image processing. Tensorflow is going to be used in building the deep learning model and all the image processing is going to be done with OpenCV-Python. So, at the end of this research a deep learning model that recognizes Ethiopian license plates with better accuracy is going to be built.

scholarly journals Performance Improvement of Electro Optic Search and Track System for Maritime Surveillance

2020 ◽  
Vol 70 (1) ◽  
pp. 66-71 ◽  
Author(s):  
Manvendra Singh ◽  
Sudhir Khare ◽  
Brajesh Kumar Kaushik
Keyword(s):  
Real Time ◽  
Marine Environment ◽  
Selection Criterion ◽  
Vital Role ◽  
Maritime Surveillance ◽  
Detection And Tracking ◽  
Track System ◽  
Electro Optic ◽  
Video Processor ◽  
Processing Techniques

Surveillance of maritime domain is absolutely vital to ensure an appropriate response against any adverse situation relating to maritime safety or security. Electro-optic search and track (EOST) system plays a vital role by providing independent search and track of potential targets in marine environment. EOST provides real-time images of objects with details, required to neutralise threats. At long range, detection and tracking capability of EOST degrades due to uncertainty in target signatures under cluttered scenario. Image quality can be improved by using suitable sensors and enhancement using the target/background signature knowledge. Robust tracking of object can be achieved by optimising the performance parameters of tracker. In the present work, improvement in the performance of EOST subsystems such as sensor, video processor and video tracker are discussed. To improve EOST performance in terms of detection and tracking, sensor selection criterion and various real time image processing techniques and their selection criteria for maritime applications have been also discussed. Resultant improvement in the quality of image recorded under marine environment has been presented.

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