Gradient-Enhancing Conversion for Illumination-Robust Lane Detection

Yoo, Hunjae; Yang, Ukil; Sohn, Kwanghoon

doi:10.1109/tits.2013.2252427

Cited by 192 publications

(105 citation statements)

References 18 publications

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“…Some gradient based algorithms can be commonly found in the literature, e.g., Sobel edge detector with symmetrical local threshold [93], adaptive thresholding [91], and gradient-enhancing conversion [94]. However, these algorithms are sensitive to noise and can result in a large number of outliers from clutter and shadows.…”

Section: Lane Line Marking Detectionmentioning

confidence: 99%

Perception, Planning, Control, and Coordination for Autonomous Vehicles

et al. 2017

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Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed.

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Section: Lane Line Marking Detectionmentioning

confidence: 99%

Perception, Planning, Control, and Coordination for Autonomous Vehicles

et al. 2017

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“…Yoo et al [11] generates lane gradient maximized image from a color image based on linear discriminant analysis. This produces strong edges to the lane boundary in various illumination.…”

Section: Lane Detection and Tracking Algorithmsmentioning

confidence: 99%

Review of Lane Detection and Tracking Algorithms in Advanced Driver Assistance System

Kumar¹,

Simon²

2015

IJCSIT

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“…This method mainly oriented to structured road with the corresponding road model according to the lane line shape. For example, Yoo et al [4] presented a piecewise linear model based on Hough transform. Model based method is able to ensure good recognition accuracy, but the recognition effect is poor under complex illumination conditions.…”

Section: Introductionmentioning

confidence: 99%