Image Edge Detection Using Edge Detection Operators

This article discusses various operators for image processing, specifically Sobel, Roberts, and Laplace operators. These operators are primarily used for edge detection and image enhancement applications. The Sobel operator utilizes convolution with 3x3 kernels to detect horizontal and vertical edges by calculating gradient approximations. The Roberts operator employs 2x2 cross-difference kernels for detecting diagonal edges with high sensitivity to noise. The Laplace operator uses second-order derivatives for zero-crossing detection, effectively identifying rapid intensity changes in images. Through these operators, we can extract detailed image features and optimize them according to specific requirements. In code implementation, these operators typically involve convolution operations with specific kernels, followed by thresholding to generate binary edge maps. The performance can be enhanced by combining with Gaussian smoothing for noise reduction or using non-maximum suppression for edge thinning.