Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{151905,
        author = {Raman Shukla and Rajat Shukla and Sarthak Garg and Sharad Singh and Pooja Vajpayee},
        title = {Lane line Detection System in Python using OpenCV},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {1213-1216},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151905},
        abstract = {During the driving operation, humans use their optical vision for vehiclemaneuvering. The road lane marking, act as a constant reference for vehicle navigation. One of the prerequisites to have in a self-driving car is thedevelopment of an Automatic Lane Detection system using an algorithm. 
Computer vision is a technology that can enable cars to make sense of their surroundings. It is a branch of artificial intelligence that enables software to understand the content of image and video. Modern computer vision has come a long way due to the advances in deep learning, which enables it to recognize different objects in images by examining and comparing millions of examples and cleaning the visual patterns that define each object. While especially efficient for classification tasks, deep learning suffers from serious limitations and can fail in unpredictable ways. 
This means that a driverless car might crash into a truck in broad daylight, or worse, accidentally hit a pedestrian. The current computer vision technology used in autonomous vehicles is also vulnerable to adversarial attacks, by manipulating the AI’s input channels to force it to make mistakes. For instance, researchers have shown they can trick a self-driving 
car to avoid recognizing stop signs by sticking black and white labels on them.
},
        keywords = {Deeplearning(DL), MachineLearning(ML),Convolutionalneuralnetworks, Computer Vision.},
        month = {},
        }