Hough Transform for Line Detection

While the Hough transform method shows good performance in line detection, we can explore additional approaches to improve detection accuracy and efficiency. For instance, implementing image preprocessing techniques including Gaussian smoothing and Canny edge detection can better prepare the image for line identification. The preprocessing phase typically involves using OpenCV functions like cv2.GaussianBlur() for noise reduction and cv2.Canny() for edge enhancement. Furthermore, we can leverage deep learning technologies such as Convolutional Neural Networks (CNNs) to train models for more accurate line detection. This approach involves creating custom architectures or using pre-trained models with specialized layers for line feature extraction, which can significantly improve success rates in complex images. Therefore, we should continuously experiment with new methodologies and technologies to achieve better results in line detection applications.