1. Real-Time Automated Target Object Tracking System
Cleberton de Santana Oliveira
Instructor: Professor Jafar Saniie
This project is based on development of a system for
recognition, tracking and neutralization of a mobile
object invasion utilizing a Processing point of view. This
incorporates:
• Image Processing Algorithms application
• Real time serial communication between a
microcontroller and the central processor
• Automated digital control of motors system and laser
gun.
Introduction
System Overview
The interface between the computer processing and
the microcontroller is made by utilizing UART serial
communication because of the simplicity and real time
motivations.
The central computer sends the command option
through USB port to the microcontroller and the
microcontroller gives the command to the stepper
motor, servo motors, and laser gun.
Serial Communication
Image
Capture
Image Processing
and Target
recognition
Microcontroller
Stepper
Motor
Servo motors
Gun with laser
pointer
Laptop
USB Nucleo Microcontroller
To maintain the recognized object on camera view, the
camera is coupled on a rotational base with a stepper
motor.
Stepper Motor
Microcontroller Stepper Motor Driver
Stepper Motor
Pulse train
The laser gun is controlled by two servo motors from
given command of the microcontroller. As there is no
feedback to the servo motors, the natural choice was to
model the position of the object on the image with the
position angles of the servo motor.
Laser Gun and Tracking Calibration
UART
Laser gun on Servo motors control
Object position
Position-Servo modeling
 Communication Protocol working as desired
 Stepper motor control working as desired
 Servo motors control working as desired
Progress
UART Com.
PWM
Signals
Camera
Laser pointer
Brazilian Scientific Mobility Program(BSMP), Institute of International
Education(IIE), and Coordination for the Improvement of Higher
Education Personnel (CAPES)
Graduate Students: Thomas Gonnot, Yonghui Jia, Guojun Yang
Acknowledgement
Rotating Base
[1] R. Jones, I. Svalbe, “Algorithms for the Decomposition of Gray-Scale Morphological Operations”, IEEE
TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 16, NO. 6, JUNE 1994.
[2] K. Suzuki, I. Horiba, N. Sugieb,”Linear-time connected-component labeling based on sequential local
operations”, Computer Vision and Image Understanding 89 (2003) 1–23
[3] Jing-Hao Xuea, D. M. Titteringtonb, “Median-based Image Thresholding”, Image and Vision Computing
November 9, 2010.
Reference