利用人眼感知视觉模型的车型动态定位

通过对实时汽车图像的大量研究,提出基于人眼感知视觉模型的自适应汽车车体定位算法。在HSI彩色图像空间,根据人眼分辨率的视觉感知模型分别在色度、亮度和饱和度空间进行自适应的边缘检测;将3个空间得到的图像边缘合并以得到整个车体在实际影像序列中的边缘;最后利用投影知识原理,分别利用边缘的垂直投影图和水平投影图来定位车体的左右边界和上下边界。实验结果表明,该算法具有较快的速度和较好的准确性,能满足实时的车型识别系统的要求。

基于视觉模型的车型动态定位

车型识别系统(VehicleRecognitionSystem简称VRS)是智能交通的一个重要课题,文章根据实时提供的汽车图像进行了大量的研究,采用了基于视觉模型的自适应的汽车车体定位算法。该算法采用的是HSI彩色图像空间,HSI彩色空间更适合人的视觉。同时根据基于人眼分辨率的视觉模型自适应地进行汽车彩色图像的边缘检测,根据边缘的垂直投影图和水平投影图来定位车体的左右边界和上下边界,实验结果表明该算法具有较快的速度,完全能满足适时的车型识别系统的要求。

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.