This project was developed as part of a job application to demonstrate Computer Vision skills. It implements an automated system for measuring screw lengths in images using OpenCV and Python.

• Image preprocessing for enhanced screw detection
• Screw detection using contour analysis
• Accurate length measurement using Principal Component Analysis (PCA)
• Visualization of detected screws and measurements
• Statistical analysis of screw lengths across multiple images

• Python 3.x
• OpenCV (cv2)
• NumPy
• SciPy

1. Clone this repository
2. Install the required packages:

   pip install opencv-python numpy scipy
   

1. Place your screw images in the Schrauben/ directory
2. Run the script:

   python screw_measurement.py
   

3. Processed images will be saved in the processed_screws/ directory
4. Statistical analysis of the measurements will be printed to the console

The script includes several adjustable parameters that can be modified to optimize performance for different types of screws or image conditions:

• Minimum length threshold
• CLAHE parameters for contrast enhancement
• Thresholding method
• Morphological operation kernel size
• Contour filtering criteria
• PCA axis length multiplier

Refer to the comments in the code for details on adjusting these parameters.

• ScrewMeasurement class: Main class containing the image processing and measurement logic
• preprocess_image: Image preprocessing function
• detect_screw: Screw detection function
• measure_length: Length measurement function
• process_image: Single image processing function
• process_folder: Batch processing function for multiple images
• analyze_results: Statistical analysis function

• Implement a graphical user interface for easier use
• Add support for calibration to convert pixel measurements to real-world units
• Enhance robustness for different lighting conditions and screw types

houmairi

This project is open-source and available under the MIT License.