Universal Edge Detection Function

This article presents a universal edge detection function that enables selection among different operators through parameter inputs. The implementation supports five distinct edge detection algorithms: Sobel operator for gradient-based detection using first-order derivatives, Prewitt operator with similar convolution kernels for noise-resistant edge identification, Roberts operator utilizing cross-differences for diagonal edge detection, Marr operator (also known as Laplacian of Gaussian) for scale-space filtering, and Canny algorithm featuring multi-stage processing including Gaussian smoothing, gradient calculation, non-maximum suppression, and hysteresis thresholding. The function design employs a modular architecture where each operator is implemented as an independent module, allowing easy extension and parameter customization. Detailed design documentation is provided to facilitate understanding of the algorithm implementations, kernel configurations, and parameter optimization strategies for different edge detection scenarios.