An adaptive road ROI determination algorithm for lane detection

Ding, Dajun; Lee, Chanho; Lee, Kwang-Yeob

doi:10.1109/tencon.2013.6718807

Cited by 39 publications

(19 citation statements)

References 8 publications

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“…[1,9] Lane detection enables you to obtain the position as well as direction of the vehicle in addition lane information, as well as an area which includes highways is important to alert a driver associated with lane departure. [7] 1.2 HOUGH TRANSFORM Richard Duda and Peter Hart in 1972 was the first one to develop Hough transform. Analysis of detecting lines, curves and ellipses is globally done by Hough transform techniques.…”

Section: Lane Detectionmentioning

confidence: 99%

“…A large number of traffic accidents will be avoided if the system can warn drivers timely. Dajun Ding et al 2013 [7] In order to identify the road region, the ROI determination algorithm based on vision is suggested in this paper which uses the positional information of a vanishing point and line segments. The Hough transform is generally used for detection of road line segments.…”

Section: Related Workmentioning

confidence: 99%

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A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

Multani

Marwaha²

2017

IJECS

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This paper represents that lane coloration has become popular in real time vehicular ad-hoc system. Lane detection is normally helpful to localize path limits, determine undesired lane variations, and to enable approximation of the upcoming geometry of the road. There are different types of methods that are used for detecting lines, curves and ellipses i.e. hough transform, clustering and curve fitting. The overall objective of this paper is to providing better performance in lane coloration algorithm. The methods developed till now are working effectively as well as giving good results.

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Section: Lane Detectionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

Multani

Marwaha²

2017

IJECS

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“…We use an adaptive ROI setting method [3] in this step. We assume that the lanes are parallel to each other.…”

Section: A Lane Detectionmentioning

confidence: 99%

Various lane marking detection and classification for vision-based navigation system?

Ding

Yoo

Jung

et al. 2015

2015 IEEE International Conference on Consumer Electronics (ICCE)

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A vision-based car navigation system (CNS) gives drivers more precise and realistic traffic data than a traditional 2D-CNS. As part of the vision-based CNS, the ability to detect lane markings can provide significant warnings which increase traffic safety and convenience. Meanwhile, accurate lane classification results can indicate the current/approaching road conditions in this system. This paper concentrates on two kernels: lane marking detection and lane type identification. The lane detection part uses IPM and histogram sampling and the lane marking type classification step utilizes spatial and frequency sampling for different types of lane markings.

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“…It is known that lane lines only appear in the road region, and the road ROI(region of interest) is always needed in the first step. We use an adaptive ROI setting method [4]. The ROI is determined using the positional information of a vanishing point and line segments.…”

Section: Lane Marking Detectionmentioning

confidence: 99%

An Urban Lane Detection Method Based on Inverse Perspective Mapping

Ding

Yoo

Jung

et al. 2014

Advanced Science and Technology Letters

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Lane markings can provide drivers significant warning instruction about current/ approaching road condition, in that case precise lane marking detection results are important assistance for safety issue in the driving assistance system (DAS). In this paper, we mainly focus on urban lane marking detection. We used sampling peaks from IPM image for lane markings' extraction and description. The proposed method is applied to various video images from black box, and is verified to be robust.

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An adaptive road ROI determination algorithm for lane detection

Cited by 39 publications

References 8 publications

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

Various lane marking detection and classification for vision-based navigation system?

An Urban Lane Detection Method Based on Inverse Perspective Mapping

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