🎯 Vision-Based Object Tracking System

A real-time Vision-Based Object Tracking System built using Raspberry Pi, OpenCV, Pi Camera, HC-SR04 Ultrasonic Sensor, and PID Control. The system detects and tracks a target object while maintaining a safe following distance autonomously.

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📌 Project Overview

This project combines computer vision, distance sensing, and motion control to create an autonomous tracking robot capable of:

• Detecting target objects using camera vision
• Tracking object movement in real-time
• Maintaining safe distance automatically
• Controlling motor speed using PID
• Stopping safely when the object is lost

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🚀 Features

✅ Real-time object detection and tracking

✅ HSV-based color segmentation

✅ Distance measurement using HC-SR04

✅ PID-based motor control

✅ Differential drive movement

✅ Moving average filtering for stable readings

✅ Automatic stop when target is lost

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🛠 Hardware Used

Component	Description
Raspberry Pi 4B	Main processing unit
Pi Camera Module	Image capture
HC-SR04 Ultrasonic Sensor	Distance measurement
L298N Motor Driver	Motor control
DC Motors	Robot movement
Battery Pack	Power supply

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💻 Software Stack

• Python
• OpenCV
• Raspberry Pi GPIO
• NumPy
• PID Control Algorithm
• HSV Color Detection

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⚙ System Workflow

Start
   ↓
Capture Camera Frame
   ↓
Convert Image → HSV
   ↓
Apply Yellow Mask
   ↓
Detect Object Contours
   ↓
Calculate Object Position
   ↓
Measure Distance (Ultrasonic)
   ↓
Apply Moving Average Filter
   ↓
PID Control
   ↓
Motor Adjustment
   ↓
Robot Movement

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📷 Object Detection Method

The system uses:

1. Capture frame from Pi Camera
2. Convert image from RGB → HSV
3. Apply yellow color threshold
4. Perform erosion and dilation
5. Detect contours
6. Extract centroid position
7. Calculate tracking error
8. Control robot direction

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📏 Distance Control

Distance is measured using HC-SR04 ultrasonic sensor.

Features:

• Safe following distance: 30 cm
• Moving average filter window: 5 samples
• Noise reduction
• Stable tracking performance

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🤖 Robot Behaviour

Object Detected

• Move forward
• Adjust direction
• Maintain distance

Object Lost

• Stop motors
• Wait for object reappearance

Object Too Close

• Reduce speed
• Stop if required

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📂 Project Structure

Vision-Based-Object-Tracking-System/
│── Codes/
│   ├── Color_detect_HSV.py -- Used to read the HSV values for the required color (Yellow is our case).
│   ├── HSV.py -- Read the HSV values and print them.
│   └── Tracker.py -- Main code file
│
│── images/
│── README.md

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📈 Results

• Maintained 30 cm safe distance
• Real-time object detection
• Smooth tracking using PID
• Full horizontal tracking capability
• Stable distance filtering

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🔮 Future Improvements

• Multi-object tracking
• YOLOv8 integration
• Obstacle avoidance
• ROS2 integration
• Cloud telemetry dashboard
• Battery optimization

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📸 Hardware Setup

Components connected:

Raspberry Pi 4B
↓
Pi Camera Module
↓
HC-SR04 Sensor
↓
L298N Motor Driver
↓
Differential Drive Robot

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👨‍💻 Authors

D Mabu Jaheer Abbas

Narra Raghuvender

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📜 License

This project is developed for educational and research purposes.

MIT License