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This paper proposes a novel fast dehazing method based on dark channel prior. The dark channel prior is the phenomenon about normal outdoor images containing at least one low energy pixel around a block among three channels. It helps roughly estimating the air mediums thickness, which decreases the scene transmission. We propose a variation of optical model whose single atmospheric attenuation coefficient...
A lane-departure detection system without intrinsic and extrinsic camera parameters calibration is proposed in this paper. The proposed system, which provides driving safety by lane detection and lane departure warning, is focused on urban road with complicated lane marks instead of simple highway scenes. Due to the complexity of urban traffic scenes, false lane detections are highly caused by warning...
In this paper, we present a new methodology for detecting lane markers that is able to withstand many challenging situations like scattered shadows, illumination changes, and presence of neighboring vehicles to name a few. At first, the input image undergoes a perspective removal followed by a color space conversion. Then, the core elements consisting of template matching, lane region merging, and...
Various image processing techniques and geometric models have been applied in vision based lane detection subsystems of intelligent vehicles and Advanced Driver Assistance Systems (ADAS). However, challenging conditions such as strong shadows, occlusions, eroded markings, high curvatures are ongoing issues in this topic. In this paper, a novel lane extraction method based on symmetrical local threshold...
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...
People have a growing interest for driver assistant systems that are used to monitor the driving conditions by visual technique, and warn and guide drivers the road conditions. This paper proposes a real-time lane detection algorithm which is a necessary part for driver assistant system and unmanned vehicle. The algorithm presented in this paper integrates multiple cues, including bar filter which...
Concerning the problem of lane detection in the Lane Departure Warning (LDW) system, this paper presents one method to detect the region of lane marking based on the CIELab color features clustering. Color space can provide us more precious information than gray scale. This algorithm proves that it is feasible to recognize lane marking by using color clustering. According to the geometry feature of...
This paper proposes an effective lane detection and tracking method using statistical modeling of lane color and edge-orientation in the image sequence. At first, we will address some problem of classifying a pixel into two classes(lane or background) and detecting one exact lane. Generally, the probability of a pixel classification error conditioned on the distinctive feature vector can be decreased...
Accurate lane detection in real-time is a critical task in autonomous vehicle guidance and lane departure warning for driver assistance. Existing vision-based approaches rely mostly on some analysis of the spatial gradient of the image. However, if the road structure is not regular and well delimited, edges may not be easy to extract and other features must be employed. This paper evaluates the use...
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