Lane mark detection using Hough transform

Mariut, Felix; Foşalău, Cristian; Petrisor, Daniel

doi:10.1109/icepe.2012.6463823

Cited by 20 publications

(10 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…F. Mariut (2012) [7] proposed a simple algorithm that detects the lane marks and its characteristics and is able to determine the travelling direction. The Hough Transform was used to detect the lines in images.…”

Section: Hongli Fani and Weihua Wang (2013)mentioning

confidence: 99%

See 1 more Smart Citation

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Kaur¹,

chhabra²

2015

IJCA

View full text Add to dashboard Cite

With the increase in advent of intelligent vehicle technology, LDWS technique is actively developing to provide assistance to drivers in generating warning signal in case of lane departure. In this paper, the input image is divided into four regions of interest. Then the CLAHE is applied on the given ROI for better image contrast and removal of noise using gradient filter. Improved Hough Transform is applied on the given image for the detection of curved and straight lanes. After detecting the lanes, they are colored with green color so that they are clearly visible. The proposed algorithm is analysed based on the parameters like Accuracy, BER, Fmeasure, and Sensitivity. The analysis shows that this algorithm provides efficient and effective performance compared to the existing algorithm.

show abstract

Section: Hongli Fani and Weihua Wang (2013)mentioning

confidence: 99%

“…The Hough Transform [7] is basically used for detection of straight lanes and roads. The traditional Hough Transform can be improved for detection of curved lanes.…”

Section: Algorithm Analysismentioning

confidence: 99%

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Kaur¹,

chhabra²

2015

IJCA

View full text Add to dashboard Cite

show abstract

“…Linear-parabolic lane models are proposed for lane departure warning systems, in which the linear function and quadratic function are used to model the lane markings in the near field and far field, respectively [ 33 , 37 ]. Hough Transform (HT) and its variants (e.g., improved HT, randomized HT, hierarchical HT) are widely used for straight or curved lane marking detection [ 2 , 38 , 39 , 40 , 41 ]. However, one primary limitation of this method is how to model arbitrary road shape.…”

Section: Introductionmentioning

confidence: 99%

Lane Marking Detection and Reconstruction with Line-Scan Imaging Data

Luo

Wang

2018

Sensors

View full text Add to dashboard Cite

Lane marking detection and localization are crucial for autonomous driving and lane-based pavement surveys. Numerous studies have been done to detect and locate lane markings with the purpose of advanced driver assistance systems, in which image data are usually captured by vision-based cameras. However, a limited number of studies have been done to identify lane markings using high-resolution laser images for road condition evaluation. In this study, the laser images are acquired with a digital highway data vehicle (DHDV). Subsequently, a novel methodology is presented for the automated lane marking identification and reconstruction, and is implemented in four phases: (1) binarization of the laser images with a new threshold method (multi-box segmentation based threshold method); (2) determination of candidate lane markings with closing operations and a marching square algorithm; (3) identification of true lane marking by eliminating false positives (FPs) using a linear support vector machine method; and (4) reconstruction of the damaged and dash lane marking segments to form a continuous lane marking based on the geometry features such as adjacent lane marking location and lane width. Finally, a case study is given to validate effects of the novel methodology. The findings indicate the new strategy is robust in image binarization and lane marking localization. This study would be beneficial in road lane-based pavement condition evaluation such as lane-based rutting measurement and crack classification.

show abstract

“…The Hough transform operator detects straight lines and curves. It is the most reliable method to detect straight lines by counting each unique equation for every possible line that can be detected from each point in the image (Mariut, Fosalau, & Petrisor, 2012).…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Highway Lane Detection by Using Hough Transform Technique

Aminuddin

Ibrahim

Ali

et al. 2017

JICT

View full text Add to dashboard Cite

This paper presents the development of a road lane detection algorithm using image processing techniques. This algorithm is developed based on dynamic videos, which are recorded using on-board cameras installed in vehicles for Malaysian highway conditions. The recorded videos are dynamic scenes of the background and the foreground, in which the detection of the objects, presence on the road area such as vehicles and road signs are more challenging caused by interference from background elements such as buildings, trees, road dividers and other related elements or objects. Thus, this algorithm aims to detect the road lanes for three significant parameter operations; vanishing point detection, road width measurements, and Region of Interest (ROI) of the road area, for detection purposes. The techniques used in the algorithm are image enhancement and edges extraction by Sobel filter, and the main technique for lane detection is a Hough Transform. The performance of the algorithm is tested and validated by using three videos of highway scenes in Malaysia with normal weather conditions, raining and a night-time scene, and an additional scene of a sunny rural road area. The video frame rate is 30fps with dimensions of 720p (1280x720) HD pixels. In the final achievement analysis, the test result shows a true positive rate, a TP lane detection

show abstract

Lane mark detection using Hough transform

Cited by 20 publications

References 12 publications

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Lane Marking Detection and Reconstruction with Line-Scan Imaging Data

A New Approach to Highway Lane Detection by Using Hough Transform Technique

Contact Info

Product

Resources

About