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Traffic flow, analysis and control is gaining high relevance, as the number of circulating vehicles continuously increases. This article proposes a computer vision based platform, which automatically detects vehicles in order to infer the traffic conditions. The developed real time detection algorithm is based on a dual background subtraction technique, incorporating the one known has Codebook and...
Lane detection can provide important information for safety driving. In this paper, a real time vision-based lane detection method is presented to find the position and type of lanes in each video frame. In the proposed lane detection method, lane hypothesis is generated and verified based on an effective combination of lane-mark edge-link features. First, lane-mark candidates are searched inside...
Traffic sign detection is important to a robotic vehicle that automatically drives on roads. In this paper, an efficient novel approach which is enlighten by the process of the human vision is proposed to achieve automatic traffic sign detection. The detection method combines bottom-up traffic sign saliency region with learning based top-down features of traffic sign guided search. The bottom-up stage...
This paper implements an embedded multi-core DSP system for vehicle vision-based lane-marking tracking. A fast algorithm based on Kalman filter and boundary detection is proposed in this system. The developed system can reduce the complexity of vision data processing and meet the real-time requirements.
Nowadays roads and streets are getting overcrowded, especially in bigger cities. Hence the main goal of our project is to build a traffic monitoring system which is able to detect the movement of cars and to track and count the different vehicles by analyzing a camera picture with the help of computer vision. The real-time process (15-30 fps) of the video stream works at daylight. The traffic monitoring...
A novel vision-based road detection method was proposed in this paper to realize visual guiding navigation for ground mobile vehicles in outdoor environments. The road region was first segmented from the jumbled backgrounds by using an adaptive threshold segmentation algorithm named OTSU. Subsequently, the Canny edges extracted in grey images would be filtered in the road region so that the road boundary...
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