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@article{174281,
        author = {Akash Jaiswal and Rohit Gupta and Omkar Singh},
        title = {Road lane detection using computer vision},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3431-3434},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174281},
        abstract = {Lane detection is essential for autonomous driving and ADAS, ensuring vehicle safety by identifying road boundaries and lane markings. This paper presents a vision-based approach combining image processing and machine learning. The method preprocesses images with Gaussian blur, applies Canny edge detection to identify lane boundaries, and uses the Hough Transform to detect and classify lane lines. To enhance accuracy under varying conditions, color space transformations (HSV/LAB) help distinguish lane markings from the road surface. The system effectively addresses challenges like shadows and glare, with future work focusing on further improving robustness and adaptability.},
        keywords = {CNN, SVM, Image processing, Canny edge detection, ADAS, Lane Detection.},
        month = {March},
        }