🎯 Real-Time Moving Object Detection using OpenCV

A real-time moving object detection system using Python and OpenCV. The application captures a live webcam feed, detects any motion by comparing frames, and highlights moving objects with a bounding box — displaying a real-time status on screen.

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📸 Demo

The system shows "Normal" when the scene is still and "Moving Object Detected" with a green bounding box when motion is found.

[Live Camera Feed]
  → Frame 1 captured as background reference
  → Each new frame compared to background
  → Motion area highlighted with green rectangle
  → Status label updated in real-time

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⚙️ How It Works

1. Background Reference — Captures the first frame as a static background
2. Grayscale + Blur — Converts each frame to grayscale and applies Gaussian Blur to reduce noise
3. Frame Differencing — Finds the absolute difference between the background and current frame
4. Thresholding — Applies a binary threshold to isolate motion regions
5. Contour Detection — Detects contours of moving regions and draws bounding boxes

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🛠️ Tech Stack

Tool	Purpose
Python 3.x	Core programming language
OpenCV	Real-time image & video processing
imutils	Frame resizing and contour utilities

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📦 Installation

# Clone the repository
git clone https://github.com/arunkumararavindhakshan05-sudo/Moving_object_detection_using_opencv.git
cd Moving_object_detection_using_opencv

# Install dependencies
pip install opencv-python imutils

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▶️ Usage

python cameraTest.py

Controls:

• Press Q — Quit the camera feed

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📁 Project Structure

Moving_object_detection_using_opencv/
│
├── cameraTest.py       # Main script
├── .gitignore
└── README.md

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🔮 Future Improvements

• Add sensitivity/threshold configuration via command-line arguments
• Save video recording when motion is detected
• Send email/SMS alert on detection
• Multi-camera support

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👤 Author

Arunkumar Aravindhakshan 🔗 LinkedIn | GitHub