Line Detection Using Radon Transform

This text provides a basic introduction to using MATLAB's built-in Radon transform for line detection. The implementation typically involves calling MATLAB's radon() function to compute the Radon transform matrix, followed by peak detection in the transform domain to identify straight lines. The process can be enhanced through several approaches: First, comparative experiments can be conducted on different images to evaluate line detection performance across various scenarios. Second, the method can be integrated with other image processing techniques such as edge detection (using Canny or Sobel operators) and image segmentation algorithms to improve detection accuracy. Additionally, the Hough transform function (hough() and houghpeaks()) can be combined with Radon transform for more robust line identification. From an application perspective, this technique extends beyond general image processing to industrial applications like measuring straightness of machine parts in manufacturing, or assessing road linearity in transportation infrastructure. The implementation typically involves parameter optimization for the Radon transform angles and resolution settings to balance computational efficiency and detection precision. This method demonstrates significant practical value across multiple engineering domains.