Thinning Algorithm: Hilditch's Algorithm Implementation

Throughout the journey of learning computer science, we frequently encounter algorithms that are essential for writing efficient code. Among these, Hilditch's Algorithm represents a fundamental thinning technique that every beginner must master. The algorithm operates by iteratively removing boundary pixels from binary images while preserving connectivity, typically implemented using 3x3 neighborhood analysis and connectivity checks. Although the algorithm appears straightforward conceptually, understanding its underlying principles and implementation methodology provides crucial insights for comprehending and applying more complex algorithms. Key implementation aspects include boundary pixel classification, connectivity preservation rules, and iteration control until no further changes occur. During the learning process of Hilditch's Algorithm, we gain deep understanding of core concepts in image processing and computer vision domains, establishing a solid foundation for professional development. The algorithm typically involves scanning images multiple times while applying logical conditions to determine pixel deletion candidates based on their eight-connected neighbors.