Mathematical Morphology Implementation for Grayscale and Binary Image Processing

This repository contains my original MATLAB source code for mathematical morphology operations on both grayscale and binary images, implemented without relying on MATLAB's built-in functions. The core implementation includes fundamental morphological operations such as dilation using structuring element convolution, erosion through minimum value filtering within neighborhoods, and combined opening/closing operations for noise removal and gap filling. Beyond basic morphology, the code provides essential binary image processing capabilities: - Image inversion through logical complement operations - Smoothing via morphological filtering techniques - Edge detection using gradient-based morphological boundaries The algorithm implementations feature custom structuring element handling and neighborhood processing logic, ensuring educational transparency while maintaining processing efficiency. These functions enable streamlined morphological processing pipelines for more precise and efficient image analysis. Whether you're conducting image processing research or developing computer vision applications, this codebase can significantly reduce development time and effort. I hope you find it valuable and applicable to your projects!