Implementation of Radon Transform for Direct Detection of Edge Positions and Strengths in Images

The Radon transform serves as a crucial algorithm for edge detection in digital images. This algorithm operates by computing line integrals along various orientations through the image matrix, enabling direct determination of edge positions and their corresponding intensity strengths. In MATLAB implementation, the radon() function calculates projections of the image intensity along specified angles, typically using a discrete approach that samples the image along parallel beams. Edge detection plays a fundamental role in image processing workflows, as it facilitates the extraction of significant features and boundary information from visual data. By utilizing this MATLAB program that implements the Radon transform, researchers and engineers can effectively analyze edge structures within images through the transform's projection data, which reveals line features across different orientations. The implementation typically involves specifying theta vectors for projection angles and analyzing the resulting sinogram to identify prominent edges. This enhanced understanding of edge characteristics provides valuable information for subsequent image processing and analysis tasks, making the mastery and application of this algorithm particularly significant for computer vision and medical imaging applications.