Several Common Edge Detection Operators: Sobel, Roberts, Prewitt, LoG, Canny, and Zero-Cross

Sobel, Roberts, Prewitt, LoG (Laplacian of Gaussian), Canny, and Zero-Cross are commonly used edge detection operators, accompanied by sample detection images. Edge detection is a crucial technique in image processing that highlights object contours and boundaries, facilitating subsequent image analysis and processing tasks. These operators detect edges based on different principles and mathematical models. For instance, Sobel and Prewitt utilize gradient approximations with convolution kernels (e.g., 3x3 matrices) to compute horizontal and vertical derivatives, while Roberts applies cross-difference operators. LoG combines Gaussian smoothing with Laplacian for scale-space edge detection, and Canny employs multi-stage noise reduction, gradient calculation, non-maximum suppression, and hysteresis thresholding. Zero-Cross detects edges by identifying zero-crossings in the second derivative. Applying these operators to an image generates an edge map where high-intensity pixels indicate edge locations. In practice, selecting the appropriate operator depends on specific requirements and image characteristics. The accompanying sample images demonstrate the results of applying different operators to the same image, allowing comparison of their distinct features and performance.