The video-based traffic surveillance is widely studied nowadays. But the existing methods are always challenged by the influence of light changing, weather effects, and a large amount of computation. This paper proposed a novel method of using sequence diagram of vehicle square wave pulse to process and analyze road monitoring videos based on spatial-temporal profileaiming at providing real-time detection of traffic flow parameters and vehicle classification for intelligent transportation system (ITS). First, based on the setting of virtual detection line, this method reduces a large number of traffic monitoring videos into spatial-temporal profiles, which contain time and space information. Next, the foreground of the spatial-temporal profile is extracted to generate a vertical-projected pixel histogram. Finally, vehicle objects are detected and the traffic state parameters are calculated, including traffic flow, time headway, occupancy, vehicle speed, and vehicle classification. The analysis result shows that the proposed method can obtain traffic flow parameters quickly and accurately even with the interference of weather and light. The accuracy rate of the method is as high as 97.32%, which is efficient and practicable to satisfy the real-timeand accuracy requirements of detection of traffic flow parametersin intelligent transportation systems.