Application of Image Processing Techniques for Autonomous Cars

Shaun Fernandes, Dhruv Duseja, R. Muthalagu
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引用次数: 4

Abstract

This paper aims to implement different image processing techniques that will help to control an autonomous car. A multistage pre-processing technique is used to detect the lanes, street signs, and obstacles accurately. The images captured from the autonomous car are processed by the proposed system which is used to control the autonomous vehicle. Canny edge detection was applied to the captured image for detecting the edges, Also, Hough transform was used to detect and mark the lanes immediately to the left and right of the car. This work attempts to highlight the importance of autonomous cars which drastically increase road safety and improve the efficiency of driving compared to human drivers. The performance of the proposed system is observed by the implementation of the autonomous car that is able to detect and classify the stop signs and other vehicles.
图像处理技术在自动驾驶汽车中的应用
本文旨在实现不同的图像处理技术,以帮助控制自动驾驶汽车。使用多阶段预处理技术来准确检测车道、路标和障碍物。所提出的用于控制自动驾驶汽车的系统对从自动驾驶汽车捕获的图像进行处理。将Canny边缘检测应用于捕获的图像以检测边缘,并使用Hough变换来检测和标记汽车左右两侧的车道。这项工作试图强调自动驾驶汽车的重要性,与人类驾驶员相比,自动驾驶汽车大大提高了道路安全性并提高了驾驶效率。通过自动驾驶汽车的实现来观察所提出的系统的性能,该自动驾驶汽车能够检测和分类停车标志和其他车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.60
自引率
0.00%
发文量
12
审稿时长
18 weeks
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