Implementation of Morphological Connected Component Detection

This document describes my personal implementation of morphological connected component detection. I will provide detailed explanations of how I utilized custom-written erosion and dilation functions to achieve this objective. The methodology is fundamentally based on essential morphological operations - specifically erosion and dilation - which serve as building blocks for identifying connected regions in images. The implementation employs a sequential approach where binary images undergo iterative morphological processing to isolate distinct components. Key algorithmic aspects include using structural elements for neighborhood operations and implementing connectivity checks through pixel neighborhood analysis. During development, I incorporated additional techniques such as component labeling algorithms and boundary detection mechanisms to ensure comprehensive component identification without missing any regions. The code structure features modular function design, allowing separate testing of erosion/dilation operations before integration into the main connectivity detection routine. Through this approach, I successfully developed a reliable connected component detection method that demonstrates robustness in handling various image configurations. I hope this documentation proves valuable for researchers working in related fields of image processing and computer vision.