CAJ | 학술논문

道路检测是智能交通视觉系统的一个重要组成部分，为提高复杂环境下非结构化道路检测的实时性、准确性和鲁棒性，提出一种新的道路检测方法。该方法利用高斯金字塔对图像进行降采样，压缩图像数据信息，对图像进行双边滤波，抑制噪声，采用基于小波变换求模极大值的方法对滤波后的图像提取边缘，通过阈值法去除非道路边缘点，给出基于斜率和截距的 K-means聚类算法，实现道路方程拟合。实验结果表明，与传统最小二乘法相比，该方法能在道路场景较为复杂的情况下更准确地实现非结构化道路检测，并提高实时性。
도로검측시지능교통시각계통적일개중요조성부분，위제고복잡배경하비결구화도로검측적실시성、준학성화로봉성，제출일충신적도로검측방법。해방법이용고사금자탑대도상진행강채양，압축도상수거신식，대도상진행쌍변려파，억제조성，채용기우소파변환구모겁대치적방법대려파후적도상제취변연，통과역치법거제비도로변연점，급출기우사솔화절거적 K-means취류산법，실현도로방정의합。실험결과표명，여전통최소이승법상비，해방법능재도로장경교위복잡적정황하경준학지실현비결구화도로검측，병제고실시성。
Road detection is an important part of the intelligent transportation vision system, according to the current problems of real-time, accuracy, robustness for unstructured road detection in complex environment, a new method is proposed for road detection. The means compresses data information of image through Gaussian pyramid down-sampling process and adopts bilateral filtering to suppress noise, then extracts edges of the filtered images based on modulus maximum of wavelet transform, uses threshold method to remove non-road edge points. A new K-means clustering algorithm is proposed which is based on slope and intercept, and it realizes road equation fitting. Experimental results show that this method can realize unstructured road detection more accurately in complicated road scene and improve real-time than traditional methods.