Geometric Feature Parameter Extraction from Images

This document presents methodologies for batch processing images to extract geometric feature parameters. This approach enables comprehensive analysis of image properties through automated computer vision workflows. The implementation typically involves OpenCV or MATLAB's Image Processing Toolbox functions for edge detection (using Canny or Sobel operators) and feature extraction algorithms (like HOG or SIFT descriptors). Machine learning integration can be implemented through scikit-learn or TensorFlow for classifying extracted features using SVM or CNN architectures. The technical pipeline includes: image preprocessing (grayscale conversion, noise reduction), contour detection using findContours() functions, and geometric calculations (area, perimeter, circularity) through moment calculations. Practical applications span quality control systems, medical imaging analysis, and autonomous vehicle perception systems where batch processing efficiently handles large image datasets.