Extracting Object Boundaries from Images Using Chain Code Tracking Method

When processing input binary images, the chain code tracking method effectively extracts object boundaries from the image. Chain code tracking is a pixel connectivity-based technique that initiates from a starting point within the image and follows boundary contours according to specific directional rules until returning to the origin point. This method precisely determines object shapes and positions, providing fundamental data for subsequent image analysis and processing tasks. Through chain code implementation, developers can calculate object perimeter, area, and other shape-related features using algorithms that typically involve 8-directional or 4-directional connectivity checks. The tracking process often employs functions like finding starting points using raster scan, storing direction codes in arrays, and applying continuity conditions to ensure complete boundary closure. These extracted features provide critical information for advanced computer vision applications such as image recognition and object detection, enabling more accurate pattern analysis and machine learning model inputs.