Enhanced Lane Detection Using Otsu-Canny Edge Detection and Hough Transform

Lane detection is crucial for ensuring safe vehicle navigation. This study presents an improved lane detection algorithm aimed at enhancing accuracy and reliability. The approach begins with pre-processing the road image, incorporating grayscale conversion, histogram equalization, median filtering, and Canny edge detection to refine image quality. Next, the Region of Interest (ROI) is extracted to focus on relevant lane features. Finally, Hough Transform is applied for lane line fitting. To improve edge detection precision, the Otsu algorithm is employed for adaptive thresholding in the Canny edge detection process. Experimental results demonstrate the effectiveness of this approach in accurately identifying lane lines under varying conditions.