Boundary-Based Contour Extraction for Finger Tip and Root Detection Using Curvature Algorithm

In this paper, we implement a boundary-based contour extraction method combined with curvature algorithms to detect potential finger tip and finger root positions. The program effectively identifies finger segment regions by calculating curvature values along the extracted contour - high curvature points typically correspond to finger tips while valley points indicate finger roots. This approach proves highly effective for precise finger localization, significantly enhancing gesture recognition and control systems. The curvature calculation can be implemented using derivative-based methods (e.g., first/second derivatives of contour points) or angle-based approaches between consecutive contour segments. Furthermore, the system allows integration of additional algorithms like curvature thresholding, smoothing filters, or machine learning classifiers to optimize detection accuracy and robustness. Key functions would include contour extraction using boundary tracing algorithms, curvature computation via differential geometry methods, and peak detection for identifying extremum points along the curvature profile.