具有视觉导航功能的智能汽车图像处理算法研究

Lv Ning, Niu Shu-yan, L. Xinran
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引用次数: 4

摘要

本文以飞思卡尔的智能汽车为背景,采用摄像头作为路径检测传感器,对装载在智能车上的摄像头获取的图像进行预先扫描,并对其进行处理。首先,当由于光线不足等原因导致图像对比度不明显时,本文采用亚线性变换对图像进行处理。针对中值滤波在图像边缘点处理失败的问题,本文提出了一种带t形窗的中值滤波算法,从实验得到的结果来看,该滤波算法不仅可以滤除边缘噪声,而且更有利于对整个图像进行滤波,使图像边缘更加连续和平滑。对于图像分割,参考Sobel算子的高计算速度和Roberts算子的高精度,本文提出了一种改进的边缘检测融合算法,将这两种算子融合在一起,该融合算法更适合图像分割。实验结果表明,该检测算法的计算量远小于Sobel算子,同时可以更有效地去除孤立噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on image processing algorithm of intelligent car with visual navigation
This paper, with the background of Freescale's intelligent car using a camera as a path detection sensor to scan the path in advance, process the image got from the camera loaded on the intelligent car. First, when the image contrast is not obvious because of lack of light etc all reasons, this paper adopts sub-linear transformation to process the image. For median filter's treatment failure in case of points located on edge of image, this paper proposed an median filtering algorithm with T-shaped window, form our results obtained form experiments, we conclude that this filtering algorithm can not only filter out the noise of edge, but also more conductive to filter the whole image making the edge of image more continuous and smooth. For image segmentation, reference to Sobel operator's high computation speed and Roberts operator's high accuracy, this paper proposed an improved edge detection fusion algorithm between these two operators, this fusion algorithm is better suited to the image division. Test results show that, the amount of computation of this detection algorithm is much less than the Sobel operator, meanwhile, isolated noise can be removed more effectively using this algorithm.
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