改进的Hough变换车道检测系统,结合超分辨率重建算法和多roi

Jae-Hyun Cho, Erdenetuya Tsogtbaatar, Seong-Hoon Kim, Young-Min Jang, Pham Minh Luan Nguyen, Sang-Bock Cho
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引用次数: 8

摘要

如今,由于在车辆中使用黑匣子的需求日益增加,正在创造一个不断发展的市场;例如,在韩国,有超过100万辆汽车配备了这种设备。本文为了提高Hough变换对车道检测的识别能力,对算法进行了改进,通过设置多个感兴趣点来降低错误率,并将无法识别的外部物体部分作为车道。并应用超分辨率重建对图像进行校正。通过本文提出的算法,本文提出的算法提高了0.6%的车道识别率,并通过设置多roi对不规则部分道路不进行识别,从而显著降低了车道检测的错误率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved lane detection system using Hough transform with super-resolution reconstruction algorithm and multi-ROI
Nowadays, due to the increasing need for using black boxes in vehicles, an evolving market is being created; that for example in South Korea, more than 1 million vehicles have been equipped with this device. In this paper, in order to improve the lane detection recognition via Hough transform, we improved the algorithm by set multi-ROI to reduce error rates and unrecognized part of the outside something as a lane. And we applied super-resolution reconstruction to correct the image. Through the proposed algorithm, proposed algorithm increase 0.6% of lane recognition rate and by setting multi-ROI irregular part of the road does not recognize so lane detection error rate was reduced significantly.
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