基于OpenCV的地面停车诱导系统研究  

Research on Ground Parking Guidance System Based on OpenCV

作　　者：刘派 廖寿敏 张丽[1] 张兴 袁龙 杨世军 LIU Pai;LIAO Shoumin;ZHANG Li;ZHANG Xing;YUAN Long;YANG Shijun(School of Traffic and Transportation,Northeast Forestry University,Harbin 150040,China)

机构地区：[1]东北林业大学交通学院,哈尔滨150040

出　　处：《森林工程》2021年第3期119-125,共7页Forest Engineering

基　　金：国家重点研发计划项目(2018YFB1600900);国家级大学生创新训练项目(202010225044)。

摘　　要：为解决城市交通中存在的停车难问题,本研究提出基于计算机视觉和机器学习软件库(OpenCV)的地面停车诱导系统,以某露天停车场为例,开展实地测试,分析设备的拍摄角度、拍摄高度和级联分类器个数对设备识别效果的影响。试验结果表明,设备的拍摄角度为0°、拍摄高度为10 m、级联分类器个数为6个,设备的识别效果最为理想;设备对除黑色车型的识别率(0.77)较低外,对其他颜色车型的识别率均在0.85以上,其中对白色车辆的识别率最高(0.92),车辆颜色与停车场地面颜色色差越大时,设备识别率越高。In order to solve the parking difficult problems of urban traffic,this study proposed a ground parking guidance system based on computer vision and machine learning library(OpenCV).Taking an open parking lot as an example,field tests were carried out to analyze the effects of the shooting angle,shoot height and the number of cascade classifiers on the recognition effect of equipment.The test results showed that the best recognition effect was achieved when the shooting angle of the device was 0 degrees,the shooting height was 10 m and the number of cascading classifiers was 6.Except for the low recognition rate(0.77)of black car,the recognition rate of other color cars was above 0.85,and the recognition rate for white car was the highest(0.92).The greater the color difference between the vehicle color and the parking lot ground color,the higher the device recognition rate.

关 键 词：交通工程 停车诱导系统 计算机视觉 车辆检测 移动通信 

分 类 号：U491[交通运输工程—交通运输规划与管理]