Finger Detection and Counting

This project utilizes computer vision techniques to detect and count fingers in a live video stream. It segments the hand region from the background, calculates the convex hull of the hand, and then counts the number of fingers based on the convexity defects.

Dependencies

This project requires the following Python libraries:

• cv2: OpenCV for image processing
• numpy: Numerical operations
• sklearn: For distance calculation

Ensure these dependencies are installed in your Python environment before running the project.

Getting Started

1. Clone the Repository: Clone this repository to your local machine.

2. Install Dependencies: Install the required dependencies using pip or conda.

3. Run the Program: Execute the finger_detection.py script to start the finger detection and counting process.

Usage

Upon running the program, a live video stream will open showing the detected hand and the count of fingers.

• Background Calibration: The program initially calibrates by capturing the background for the first 60 frames. During this period, ensure there are no hands in the frame.

• Hand Detection: Once the background is calibrated, the program detects and segments the hand region from the background.

• Finger Counting: Using convex hull and convexity defects, the program counts the number of fingers raised.

• Exit: Press the Esc key to exit the program.

Customization

You can customize the following parameters in the script:

• roi_top, roi_bottom, roi_left, roi_right: Region of interest (ROI) for hand detection.
• accumulated_weight: Weight for accumulating background.
• threshold: Threshold value for segmenting hand region.
• num_frames: Number of frames for background calibration.

Feel free to adjust these parameters according to your requirements.