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Road detection is the most fundamental part of autonomous vehicles. Noises caused by shadows and vehicles on the road have a great negative impact on the road detection. Our method improves the performance under the noisy environment by taking advantage of color information to determine the road curvature. A novel geometrical method is proposed in this paper to select the most matched curvature. A...
Detection of lane boundaries of a road based on the images or video taken by a video capturing device in a suburban environment is a challenging task. In this paper, a novel lane detection algorithm is proposed without considering camera parameters; which robustly detects lane boundaries in real-time especially for sub-urban roads. Initially, the proposed method fits the CIE L*a* b* transformed road...
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...
Road detection is a crucial part of autonomous driving system. Most of the methods proposed nowadays only achieve reliable results in relatively clean environments. In this paper, we combine edge detection with road area extraction to solve this problem. Our method works well even on noisy campus road whose boundaries are blurred with sidewalks and surface is often covered with unbalanced sunlight...
For realizability and real-time processing consideration, a novel vehicle classification method is proposed for heavy traffic flow multi-lanes roads, which can classify vehicles into cars, trucks and buses. In order to monitor two lanes, our system uses three cameras which are mounted overhead of the road and look down the road at an angle of about 60 degrees. Two of them focus on the two lanes respectively...
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.
This paper proposes two different methods in order to improve the performance of traffic sign detection process. These methods are used for efficient and robust detection of red or blue colored, circular, octagonal, rectangular and triangular traffic signs. Proposed methods use both color and shape features of the traffic signs. Both of the methods gather the color and edge information of the image...
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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