HSV自适应背景阴影抑制车流检测

打开文本图片集

中图分类号：U491.116 文献标识码：A 文章编号：1003-8639（2026）03-0064-03

HSV Adaptive Background Shadow Suppression for Vehicle Flow Detection

Ding Xiao， Zhang Qiuqiu （School ofInformation Engineering，Zhengzhou Technologyand BusinessUniversity，Zhengzhou451450，China）

【Abstract】To address the pressing need for real-time and accurate traffic flow information in intelligent transportation systems，thispaper develops and implements an eficient androbust video-based vehicle counting system. Aimed at fixed-camera environments，a coordinated technical strategy is proposed： background subtraction serves as the core motion detection method，with adaptive background modelingandupdating，as well asvehicle shadow detectionand suppression，innovatively integrated within the HSVcolorspace.This design eliminates redundantcolor space conversions during processing，significantlyenhancing computational eficiency.Throughmorphologicalrefinement of foreground objectsand vehicle counting based on virtual detection lines，traffc flow statisticsare obtained.Experimental tests on multiple samples including both urban roads and highways show an average vehicle counting accuracy of over 96 % reaching 97% in ordinary road scenarios.These results confirm the practicalityand effectivenessof the proposed approach， offering a viable technical solution for intelligent transportation perception terminals.

【Key words】 intelligent transportation；video detection;background modeling;HSV color space;shadow removal;traffic flow statistics

0 引言

城市交通的高效运转是支撑经济社会发展和居民日常生活的重要保障。（剩余2704字）