Digital Image Processing Series

This document presents fundamental algorithms and techniques in digital image processing through practical code implementations: The series includes nine core implementations (P0401-P0409) demonstrating various image processing approaches: - P0401 implements edge detection using Prewitt operator through convolution with horizontal and vertical gradient kernels - P0402 demonstrates Laplacian of Gaussian (LoG) edge detection with multiple σ values, showing scale-space analysis effects - P0403 features Canny edge detection implementation including Gaussian smoothing, gradient calculation, non-maximum suppression, and hysteresis thresholding - P0404 covers global threshold segmentation techniques using histogram analysis and optimal threshold selection - P0405 implements watershed-based segmentation for handling complex image regions with gradient watershed transforms - P0406 performs quadtree decomposition for matrix data, recursively dividing regions based on homogeneity criteria - P0407 develops text/non-text classification using feature extraction and pattern recognition methods - P0408 applies morphological gradient operations (dilation minus erosion) for edge detection in binary images - P0409 presents a practical morphological processing case: removing PCB traces while preserving chip components using structuring elements and morphological operations These algorithms serve essential roles in image processing applications including edge detection, image segmentation, and feature extraction. Beyond these techniques, numerous other image processing algorithms exist for further exploration by interested readers seeking to deepen their understanding of digital image analysis.