The Multi-Scale Hough Transform Lane Detection Method Based on the Algorithm of Otsu and Canny

2014 ◽  
Vol 1042 ◽  
pp. 126-130 ◽  
Author(s):  
Yu Chai ◽  
Su Jing Wei ◽  
Xin Chun Li
Keyword(s):  
Hough Transform ◽  
Detection Method ◽  
Lane Detection ◽  
Transform Method ◽  
Canny Operator ◽  
The Road ◽  
Multi Scale ◽  
Lane Departure ◽  
Lane Line

In order to improve the accuracy of detecting lane for automatic vehicle driving, a method for detecting the straight part of Lane is proposed, which is the Multi-Scale Hough transform method for lane detection based on the algorithm of Otsu and Canny. First of all, by the methods of Otsu to segment image and use the morphology operation of erode and dilate to wipe off the information of roadside trees and fences to strengthen the road boundary characteristics.Then the lane edge and feature is gained by the canny operator. At last, using Standard Hough Transform, Progressiveness Probabilities Hough Transform and Multi-Scale Hough Transform complete the detection of lane’s straight part. The experimental results show that, Multi-Scale Hough Transform method can accurately detect the lane line and provide the reliable basis for the path planning, automatic follow-up vehicle driving and lane departure warning.

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.

scholarly journals Detection method for auto guide vehicle’s walking deviation based on image thinning and Hough transform

2019 ◽  
Vol 52 (3-4) ◽  
pp. 252-261 ◽  
Author(s):  
Xiaohua Cao ◽  
Daofan Liu ◽  
Xiaoyu Ren
Keyword(s):  
Hough Transform ◽  
Detection Method ◽  
Detection Algorithm ◽  
Visual Navigation ◽  
Guide Line ◽  
Actual Environment ◽  
Lane Line ◽  
Image Thinning ◽  
High Level ◽  
Refinement Algorithm

Auto guide vehicle’s position deviation always appears in its walking process. Current edge approaches applied in the visual navigation field are difficult to meet the high-level requirements of complex environment in factories since they are easy to be affected by noise, which results in low measurement accuracy and unsteadiness. In order to avoid the defects of edge detection algorithm, an improved detection method based on image thinning and Hough transform is proposed to solve the problem of auto guide vehicle’s walking deviation. First, the image of lane line is preprocessed with gray processing, threshold segmentation, and mathematical morphology, and then, the refinement algorithm is employed to obtain the skeleton of the lane line, combined with Hough detection and line fitting, the equation of the guide line is generated, and finally, the value of auto guide vehicle’s walking deviation can be calculated. The experimental results show that the methodology we proposed can deal with non-ideal factors of the actual environment such as bright area, path breaks, and clutters on road, and extract the parameters of the guide line effectively, after which the value of auto guide vehicle’s walking deviation is obtained. This method is proved to be feasible for auto guide vehicle in indoor environment for visual navigation.

scholarly journals A NEW APPROACH TO HIGHWAY LANE DETECTION BY USING HOUGH TRANSFORM TECHNIQUE

2017 ◽  
Author(s):  
Nur Shazwani Aminuddin ◽  
Masrullizam Mat Ibrahim ◽  
Nursabillilah Mohd Ali ◽  
Syafeeza Ahmad Radzi ◽  
Wira Hidayat Mohd Saad ◽  
...  
Keyword(s):  
Hough Transform ◽  
Average Rate ◽  
Lane Detection ◽  
Frame Rate ◽  
Video Frame ◽  
Night Time ◽  
The Road ◽  
Main Technique ◽  
On The Road ◽  
Width Measurements

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  average rate of 0.925 and the capability to be used in the final application implementation.  

A multi-scale plane-detection method based on the Hough transform and region growing

2016 ◽  
Vol 31 (154) ◽  
pp. 166-192 ◽  
Author(s):  
Xiaoxu Leng ◽  
Jun Xiao ◽  
Ying Wang
Keyword(s):  
Hough Transform ◽  
Detection Method ◽  
Region Growing ◽  
Multi Scale

scholarly journals A Lane Detection Method Based on a Ridge Detector and Regional G-RANSAC

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4028 ◽  
Author(s):  
Lu ◽  
Xu ◽  
Shan ◽  
Liu ◽  
Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Random Sample ◽  
Detection Method ◽  
Lane Detection ◽  
Feature Points ◽  
True Positive ◽  
Lane Departure ◽  
Different Types ◽  
Aerial View ◽  
Random Sample Consensus

Lane detection plays an important role in improving autopilot’s safety. In this paper, a novel lane-division-lines detection method is proposed, which exhibits good performances in abnormal illumination and lane occlusion. It includes three major components: First, the captured image is converted to aerial view to make full use of parallel lanes’ characteristics. Second, a ridge detector is proposed to extract each lane’s feature points and remove noise points with an adaptable neural network (ANN). Last, the lane-division-lines are accurately fitted by an improved random sample consensus (RANSAC), termed the (regional) gaussian distribution random sample consensus (G-RANSAC). To test the performances of this novel lane detection method, we proposed a new index named the lane departure index (LDI) describing the departure degree between true lane and predicted lane. Experimental results verified the superior performances of the proposed method over others in different testing scenarios, respectively achieving 99.02%, 96.92%, 96.65% and 91.61% true-positive rates (TPR); and 66.16, 54.85, 55.98 and 52.61 LDIs in four different types of testing scenarios.

Research on Lane Departure Warning System

2014 ◽  
Vol 598 ◽  
pp. 731-735 ◽  
Author(s):  
Hui Bao Yang
Keyword(s):  
Hough Transform ◽  
Warning System ◽  
Region Of Interest ◽  
Lane Departure Warning ◽  
Linear Mode ◽  
Detection And Tracking ◽  
Lane Departure ◽  
Calculation Parameter ◽  
Lane Line ◽  
Lane Position

Lane departure warning system includes lane identification and lane departure determination. Lane identification is crucial for lane departure warning system. In this paper, A linear mode which can only bring out small distance error and angle error is used to detect lane boundaries. A region of interest (ROI) appropriate is set to reduce nonessential cost of computation. According to the characteristics of lane position, we improve the Hough transform, reduce the detection and tracking transform angle and raise the speed of calculation. Parameter angle form Hough transform is used to lane departure determination, this method does not calibrate the camera and can get the lane departure rate. Experiments show that the system is well to detect and track the lane line and give alarm correctly.

Highway Lane Detection Based on a New Gray Method

2014 ◽  
Vol 1044-1045 ◽  
pp. 1553-1557
Author(s):  
Yan Zhou Peng ◽  
Hong Feng Gao
Keyword(s):  
Hough Transform ◽  
Color Image ◽  
Lane Detection ◽  
Gray Level ◽  
The Novel ◽  
Threshold Values ◽  
Transform Method ◽  
Illumination Changes ◽  
Canny Edge ◽  
Gray Level Image

a new gray method is provided in this paper for highway lane detection. Firstly, the novel gray method transform an RGB color image to a gray-level image based on a new gray vector. To deal with illumination changes, the new gray vector is updated on real-time.Secondly,the canny edge detector’s threshold values are decided adaptive.Lastly,Hough transform method realizes the detection of lanes. For different time in a day, experiments indicate that the proposed algorithm has good results.

scholarly journals Research on Lane Detection Based on Global Search of Dynamic Region of Interest (DROI)

2020 ◽  
Vol 10 (7) ◽  
pp. 2543 ◽  
Author(s):  
Jianjun Hu ◽  
Songsong Xiong ◽  
Yuqi Sun ◽  
Junlin Zha ◽  
Chunyun Fu
Keyword(s):  
Region Of Interest ◽  
Global Search ◽  
Lane Detection ◽  
Vehicle Speed ◽  
Feature Points ◽  
The Road ◽  
Detection Approach ◽  
Polar Coordinate ◽  
Previous Frame ◽  
Lane Line

A novel lane detection approach, based on the dynamic region of interest (DROI) selection in the horizontal and vertical safety vision, is proposed to improve the accuracy of lane detection in this paper. The curvature of each point on the edge of the road and the maximum safe distance, which are solved by the lane line equation and vehicle speed data of the previous frame, are used to accurately select the DROI at the current moment. Next, the global search of DROI is applied to identify the lane line feature points. Subsequently, the discontinuous points are processed by interpolation. To fulfill fast and accurate matching of lane feature points and mathematical equations, the lane line is fitted in the polar coordinate equation. The proposed approach was verified by the Caltech database, under the premise of ensuring real-time performance. The accuracy rate was 99.21% which is superior to other mainstream methods described in the literature. Furthermore, to test the robustness of the proposed method, it was tested in 5683 frames of complicated real road pictures, and the positive detection rate was 99.07%.

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