scholarly journals A Precise Lane Detection Algorithm Based on Top View Image Transformation and Least-Square Approaches

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Byambaa Dorj ◽  
Deok Jin Lee
Keyword(s):  
Detection Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Least Square ◽  
Parabolic Model ◽  
Image Transformation ◽  
Driver Assistance Systems ◽  
View Transformation ◽  
Lane Keeping ◽  
Top View

The next promising key issue of the automobile development is a self-driving technique. One of the challenges for intelligent self-driving includes a lane-detecting and lane-keeping capability for advanced driver assistance systems. This paper introduces an efficient and lane detection method designed based on top view image transformation that converts an image from a front view to a top view space. After the top view image transformation, a Hough transformation technique is integrated by using a parabolic model of a curved lane in order to estimate a parametric model of the lane in the top view space. The parameters of the parabolic model are estimated by utilizing a least-square approach. The experimental results show that the newly proposed lane detection method with the top view transformation is very effective in estimating a sharp and curved lane leading to a precise self-driving capability.

Lane Detection Based on Improved Canny Detector and Least Square Fitting

2013 ◽  
Vol 765-767 ◽  
pp. 2383-2387 ◽  
Author(s):  
Guang Hua Chen ◽  
Wen Zhou ◽  
Feng Jiao Wang ◽  
Bin Jie Xiao ◽  
Sun Fang Dai
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Least Square ◽  
Edge Detector ◽  
Canny Edge Detector ◽  
Least Square Fitting ◽  
Video Images ◽  
Canny Edge ◽  
Single Pixel

The video images of road monitoring system contain noise, which blurs the difference between the lane and the background. The lane detection algorithm based on traditional Canny edge detector hardly detects the single-pixel lane accurately and it produces pseudo lane. The paper proposes an effective lane detection method based on improved Canny edge detector and least square fitting. The proposed method improves the dual-threshold selection of traditional Canny detector by using the histogram concavity analysis, which sets the optimal threshold automatically. The least square method is used to fit the feature points of detected edges to accurate and single-pixel wide lane. Experimental results show that the proposed method detects the lane of video images accurately in the noise environment.

Research on the Lane Detection Algorithm Based on Zoning Hough Transformation

2012 ◽  
Vol 490-495 ◽  
pp. 1862-1866 ◽  
Author(s):  
Chao Fan ◽  
Li Long Hou ◽  
Shuai Di ◽  
Jing Bo Xu
Keyword(s):  
Hough Transform ◽  
Ambient Noise ◽  
Detection Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Dominant Position ◽  
Hough Transformation ◽  
The Road ◽  
Lane Marking ◽  
Sobel Operators

In order to improve the adaptability of the lane detection algorithm under complex conditions such as damaged lane lines, covered shadow, insufficient light, the rainy day etc. Lane detection algorithm based on Zoning Hough Transform is proposed in this paper. The road images are processed by the improved ±45° Sobel operators and the two-dimension Otsu algorithm. To eliminate the interference of ambient noise, highlight the dominant position of the lane, the Zoning Hough Transform is used, which can obtain the parameters and identify the lane accurately. The experiment results show the lane detection method can extract the lane marking parameters accurately even for which are badly broken, and covered by shadow or rainwater completely, and the algorithm has good robustness.

CORRIDOR DETECTION AND TRACKING FOR VISION-BASED DRIVER ASSISTANCE SYSTEM

2011 ◽  
Vol 25 (02) ◽  
pp. 253-272 ◽  
Author(s):  
RUYI JIANG ◽  
REINHARD KLETTE ◽  
TOBI VAUDREY ◽  
SHIGANG WANG
Keyword(s):  
Euclidean Distance ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Distance Transform ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Detection And Tracking ◽  
Algorithm Comparison ◽  
Public Dataset ◽  
Assistance Systems

A significant component of driver assistance systems (DAS) is lane detection, and has been studied since the 1990s. However, improving and generalizing lane detection solutions proved to be a challenging task until recently. A (physical) lane is defined by road boundaries or various kinds of lane marks, and this is only partially applicable for modeling the space an ego-vehicle is able to drive in. This paper proposes a concept of (virtual) corridor for modeling this space. A corridor depends on information available about the motion of the ego-vehicle, as well as about the (physical) lane. This paper also suggests a modified version of Euclidean Distance Transform (EDT), named Row Orientation Distance Transform (RODT), to facilitate the detection of corridor boundary points. Then, boundary selection and road patch extension are applied as post-processing. Moreover, this paper also informs about the possible application of corridor for driver assistance. Finally, experiments using images from highways and urban roads with some challenging road situations are presented, illustrating the effectiveness of the proposed corridor detection algorithm. Comparison of lane and corridor on a public dataset is also provided.

scholarly journals RS-Lane: A Robust Lane Detection Method Based on ResNeSt and Self-Attention Distillation for Challenging Traffic Situations

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ronghui Zhang ◽  
Yueying Wu ◽  
Wanting Gou ◽  
Junzhou Chen
Keyword(s):  
Detection Method ◽  
Autonomous Driving ◽  
Lane Detection ◽  
Feature Representation ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems ◽  
Light And Shadow ◽  
Instance Segmentation

Lane detection plays an essential part in advanced driver-assistance systems and autonomous driving systems. However, lane detection is affected by many factors such as some challenging traffic situations. Multilane detection is also very important. To solve these problems, we proposed a lane detection method based on instance segmentation, named RS-Lane. This method is based on LaneNet and uses Split Attention proposed by ResNeSt to improve the feature representation on slender and sparse annotations like lane markings. We also use Self-Attention Distillation to enhance the feature representation capabilities of the network without adding inference time. RS-Lane can detect lanes without number limits. The tests on TuSimple and CULane datasets show that RS-Lane has achieved comparable results with SOTA and has improved in challenging traffic situations such as no line, dazzle light, and shadow. This research provides a reference for the application of lane detection in autonomous driving and advanced driver-assistance systems.

Lane Detection Based on Least Square Fitting

2011 ◽  
Vol 403-408 ◽  
pp. 4068-4072
Author(s):  
Jie Hou ◽  
Zhi Tao Xiao ◽  
Fang Zhang
Keyword(s):  
Detection Algorithm ◽  
Detection Performance ◽  
Image Contrast ◽  
Lane Detection ◽  
Least Square ◽  
Intelligent Vehicle ◽  
Image Preprocessing ◽  
Least Square Fitting ◽  
Detection Algorithms ◽  
Monocular Camera

Lane detection is a key technique for intelligent vehicle driving. Aiming at the detection performance of existing lane detection algorithms, based on least square fitting, we propose a lane detection algorithm for structural road. The lane videos are gotten by the monocular camera installed in the car. Image preprocessing is applied to improve image contrast and then the image is segmented by improved Otsu. At last, the current lanes are extracted and equations are rebuilt by the least square fitting. The experiment results show that the proposed method has better accuracy and robustness compared to existing lane detection algorithms.

Lane detection algorithm based on morphological structure-elements model

2009 ◽  
Vol 29 (2) ◽  
pp. 440-443 ◽  
Author(s):  
Tao LEI ◽  
Yang-yu FAN ◽  
Xiao-peng WANG ◽  
Lü-cheng WANG
Keyword(s):  
Morphological Structure ◽  
Detection Algorithm ◽  
Lane Detection

scholarly journals Low Complexity Lane Detection Methods for Light Photometry System

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1665
Author(s):  
Jakub Suder ◽  
Kacper Podbucki ◽  
Tomasz Marciniak ◽  
Adam Dąbrowski
Keyword(s):  
Edge Detection ◽  
Optimal Path ◽  
Color Space ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Detection Methods ◽  
Raspberry Pi ◽  
Line Detection ◽  
Hsv Color Space

The aim of the paper was to analyze effective solutions for accurate lane detection on the roads. We focused on effective detection of airport runways and taxiways in order to drive a light-measurement trailer correctly. Three techniques for video-based line extracting were used for specific detection of environment conditions: (i) line detection using edge detection, Scharr mask and Hough transform, (ii) finding the optimal path using the hyperbola fitting line detection algorithm based on edge detection and (iii) detection of horizontal markings using image segmentation in the HSV color space. The developed solutions were tuned and tested with the use of embedded devices such as Raspberry Pi 4B or NVIDIA Jetson Nano.

Sign in / Sign up

Export Citation Format

Share Document