Line Detection Using Radon Transform with MATLAB Implementation

Line detection using Radon transform is a mathematically-principled image processing method that effectively identifies straight lines within images. This technique finds applications across multiple domains including medical imaging, autonomous driving systems, and robotic vision. The provided MATLAB implementation enables users to easily apply and optimize this method through key functions such as radon() and iradon() for forward and inverse transformations. Implementation considerations include parameter tuning for theta angles (typically 0:179 degrees) and optimization strategies for reducing false positives while improving detection accuracy through threshold adjustment and peak identification algorithms. Furthermore, this approach can be integrated with complementary image processing techniques like edge detection (using Canny or Sobel operators) and Hough transform to achieve more efficient and precise image analysis results. The code includes practical examples of preprocessing steps such as image binarization and noise reduction to enhance line detection performance in real-world scenarios.