自适应的SILTP算法在运动车辆检测中的研究  

Vehicle Detection Research Based on Adaptive SILTP Algorithm

作　　者：李飞[1] 张小洪[1] 赵晨丘 鄢萌[1] 

机构地区：[1]重庆大学软件学院,重庆401331

出　　处：《计算机科学》2016年第6期294-297,共4页Computer Science

基　　金：形状的语义结构表示及其分类学习研究(61173131)资助

摘　　要：为了提高复杂背景下运动车辆的检测效率,结合SILTP算法提出了一种自适应的SILTP算法。首先,对运动车辆图像进行二维离散小波变换,提取出两次低通滤波后的图像。其次,通过自适应的SILTP算法获得图像的纹理信息。然后,利用高斯混合模型进行背景建模,进而利用新图像的纹理信息动态更新背景。最后,与背景模型进行比较来获得运动车辆。对公路上运动车辆的测试表明,该检测算法在复杂背景尤其是树叶抖动等情况下能够取得较高的检测率,具有良好的自适应性。This paper presented an adaptive SILTP algorithm based on the SILTP algorithm to improve the efficiency of vehicle detection in complex background. The vehicle detection starts with a two-dimensional discrete wavelet trans- form for the image. The next steps of vehicle detection include extracting the vehicle images＇ information texture with the adaptive SILTP algorithm, using Gauss mixture model for background modeling, and using the texture information of the new image to update background dynamically. Finally, moving vehicle is obtained by comparing with the back-ground model. The results demonstrate that this detection algorithm can achieve high detection efficiency under a complex background , and has strong adaptability.

关 键 词：局部纹理特征 背景建模 车辆检测 自适应SILTP算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]