Hough Transform for Line Detection Implementation

Using MATLAB for Hough transform-based line detection provides an effective approach to identify straight lines in digital images. We have enhanced the original implementation by correcting algorithmic errors and incorporating additional features for better performance. This refined version includes optimized parameter tuning for the Hough voting process, improved edge detection preprocessing using Canny algorithm, and enhanced peak detection in Hough space for more accurate line identification. The code now features robust input validation, error handling mechanisms, and supports various image formats through MATLAB's image processing toolbox. The implementation calculates the Hough transform matrix efficiently using vectorized operations, applies non-maximum suppression to detect dominant lines, and converts detected peaks back to line parameters (rho and theta) with sub-pixel accuracy. You can now seamlessly execute this code and integrate it into your computer vision projects. These improvements significantly boost processing efficiency while delivering superior detection accuracy and user experience.