基于Top-Hat-Canny的汽车前视摄像头图像边缘检测方法研究

针对汽车前视摄像头(Forward View Camera)拍摄存在噪声及光照不均匀的问题,提出一种基于顶帽算法TopHat Canny的多重边缘检测图像预处理方法。通过对前视摄像头拍摄的道路行人、车辆及障碍物的图片进行分析,采用小波阈值算法分别对彩色图像(Red-Green-Blue,RGB)3个空间分量进行滤波去噪,并经加权平均法对重组的3个分量灰度化处理后,采用Top-Hat-Canny多重边缘检测方法对图像进行处理。实验仿真结果表明:该方法可以有效地解决噪声及光照不均对图像边缘检测带来的影响,为后续目标识别工作提供基础。

Research on the Method of Image Edge Detection From Vehicle Forward View Camera Based on Top-Hat-Canny

In view of the problem of noise and uneven illumination in forward view camera,this paper proposes an image preprocessing method based on Top Hat Algorithm(Top Hat)-Canny multiple edge detection.This paper analyzes the image signals of pedestrians,vehicles and obstacles taken by forward view camera.The components of 3 spatial components of color image(Red-Green-Blue,RGB)are filtered and denoised by wavelet threshold algorithm.Then,after the 3 components of the reconstruction are grayed by the weighted average method,the image is processed by the Top-HatCanny multiple edge detection method.The experimental simulation results show that the method can effectively solve the impact of noise and uneven illumination on image edge detection,and provide convenience for the subsequent target recognition.