A Real-Time Lane Detection Algorithm Based on Intelligent CCD Parameters Regulation

Lane departure warning system (LDWS) has been regarded as an efficient method to lessen the damages of road traffic accident resulting from driver fatigue or inattention. Lane detection is one of the key techniques for LDWS. To overcome the contradiction between complexity of algorithm and the real-time requirement for vehicle onboard system, this paper introduces a new lane detection method based on intelligent CCD parameters regulation. In order to improve the real-time capability of the system, a CCD parameters regulating method is proposed which enhances the contrast between lane line and road surfaces and reduces image noise, so it lays a good foundation for the following lane detection. Hough transform algorithm is improved by selection and classification of seed points. Finally the lane line is extracted through some restrictions. Experimental results verify the effectiveness of the proposed method, which improves not only real-time capability but also the accuracy of the system.

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A Novel Real-Time Lighting-Invariant Lane Departure Warning System

Security and Privacy in Smart Sensor Networks - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-5736-4.ch011 ◽

2018 ◽

pp. 231-252

Author(s):

Yassin Kortli ◽

Mehrez Marzougui ◽

Mohamed Atri

Keyword(s):

Real Time ◽

Traffic Accidents ◽

Essential Element ◽

Warning System ◽

Lane Detection ◽

Accuracy Evaluation ◽

Lane Departure Warning ◽

Lighting Conditions ◽

Lane Departure ◽

Driving Assistance

In recent years, in order to minimize traffic accidents, developing driving assistance systems for security has attracted much attention. Lane detection is an essential element of avoiding accidents and enhancing driving security. In this chapter, the authors implement a novel real-time lighting-invariant lane departure warning system. The proposed methodology works well in different lighting conditions, such as in poor conditions. The experimental results and accuracy evaluation indicates the efficiency of the system proposed for lane detection. The correct detection rate averages 97% and exceeds 95.6% in poor conditions. Furthermore, the entire process has only 29 ms per frame.

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Real-time illumination invariant lane detection for lane departure warning system

Expert Systems with Applications ◽

10.1016/j.eswa.2014.10.024 ◽

2015 ◽

Vol 42 (4) ◽

pp. 1816-1824 ◽

Cited By ~ 90

Author(s):

Jongin Son ◽

Hunjae Yoo ◽

Sanghoon Kim ◽

Kwanghoon Sohn

Keyword(s):

Real Time ◽

Warning System ◽

Lane Detection ◽

Lane Departure Warning ◽

Illumination Invariant ◽

Lane Departure

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Lane Detection and Lane Departure Warning System

International Journal of Advanced Trends in Computer Science and Engineering ◽

10.30534/ijatcse/2021/1021032021 ◽

2021 ◽

Vol 10 (3) ◽

pp. 2212-2218

Keyword(s):

Autonomous Vehicles ◽

Warning System ◽

Region Of Interest ◽

Detection Algorithm ◽

Lane Detection ◽

Road Accidents ◽

Lane Departure ◽

Clustering And Classification ◽

Canny Edge ◽

Boundary Information

Lane detection is important for autonomous vehicles. For this reason, many approaches use lane boundary information to locate the vehicle inside the street, or to integrate GPS-based localization. Advanced driverassistance systems are developed to assist drivers in the driving process reducing road accidents. In this work, we present an end-to-end system for lane identification, clustering and classification, based on two cascaded neural networks, that runs in real-time. The first step is camera calibration which is used to remove the effect of lens distortion. Then a canny edge detection algorithm finds the edges of the images. Then the region of interest (ROI) is selected. The ROI is actually based on the rectangular shape appearing at the bottom of the image. ROI removes the unwanted region in the image. The potential lane markers are then determined using the Hough transform to analyze lane boundaries. Once the lane pixels are found, these pixels are continuously scanned to obtain the best linear regression analysis.It is qualified to be applied on highways and urban roadways. It also has been successfully verified in sunny, and rainy conditions for both day and night.

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Robust lane detection algorithm based on triangular lane model

Filomat ◽

10.2298/fil1805639p ◽

2018 ◽

Vol 32 (5) ◽

pp. 1639-1647

Author(s):

Young Park ◽

Sung Na ◽

Qun Wei ◽

Ki Seong ◽

Jyung Lee ◽

...

Keyword(s):

Extraction Method ◽

Industrial Revolution ◽

Near Field ◽

Warning System ◽

Detection Algorithm ◽

Lane Detection ◽

Feature Points ◽

Lane Departure ◽

Cloudy Weather ◽

Forward Collision Warning

Recently, various technologies and sciences are developed for fourth industrial revolution which includes artificial intelligence, robotics, internet of things, 3-D printing, and autonomous transportation. The autonomous transportation is one of the fourth industrial technology, and has been studying for safety driving. Accurate lane detection and lane departure warning system is very important for autonomous transportation. However, conventional methods have some problems of applying real-driving such as extracting miss lanes under cloudy weather and vehicle disturbance situations. In order to solve the real driving problems, we propose a new lane detection technique for lane departure and forward collision warning system using a single in-vehicle camera. The proposed method consists of triangular lane model, feature points extraction method. In the near field, a triangular lane model is used to approximate a pair of lane boundaries. Subsequently, feature points extraction method based on hyperbola curve model is applied to obtain lane curvature in the far field. Mathematical B-spline applied to feature points for curved lane fitting. Simulation results show that the proposed lane detection and tracking method has good performance.

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Lane Line Detection System Based on Improved Yolo V3 Algorithm

10.21203/rs.3.rs-961172/v1 ◽

2021 ◽

Author(s):

Gaoqing Ji ◽

Yunchang Zheng

Keyword(s):

Real Time ◽

Detection System ◽

Detection Algorithm ◽

Horizontal Distribution ◽

Lane Detection ◽

Cluster Center ◽

Line Detection ◽

Detection Accuracy ◽

Time Performance ◽

Lane Line

Abstract Aiming at the problems of low accuracy and poor real-time performance of Yolo v3 algorithm in lane detection, a lane detection system based on improved Yolo v3 algorithm is proposed. Firstly, according to the characteristics of inconsistent vertical and horizontal distribution density of lane line pictures, the lane line pictures are divided into s * 2S grids; Secondly, the detection scale is adjusted to four detection scales, which is more suitable for small target detection such as lane line; Thirdly, the convolution layer in the original Yolo v3 algorithm is adjusted from 53 layers to 49 layers to simplify the network; Finally, the parameters such as cluster center distance and loss function are improved. The experimental results show that when using the improved detection algorithm for lane line detection, the average detection accuracy map value is 92.03% and the processing speed is 48 fps.Compared with the original Yolo v3 algorithm, it is significantly improved in detection accuracy and real-time performance.

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Computational Intelligence-based Real-time Lane Departure Warning System Using Gabor Features

2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) ◽

10.1109/apsipaasc47483.2019.9023213 ◽

2019 ◽

Author(s):

Ricky Sutopo ◽

Teo Ting Yau ◽

Joanne Mun-Yee Lim ◽

KokSheik Wong

Keyword(s):

Real Time ◽

Computational Intelligence ◽

Warning System ◽

Lane Departure Warning ◽

Lane Departure ◽

Gabor Features

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A Portable Vision-Based Real-Time Lane Departure Warning System: Day and Night

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2008.2006618 ◽

2009 ◽

Vol 58 (4) ◽

pp. 2089-2094 ◽

Cited By ~ 68

Author(s):

Pei-Yung Hsiao ◽

Chun-Wei Yeh ◽

Shih-Shinh Huang ◽

Li-Chen Fu

Keyword(s):

Real Time ◽

Warning System ◽

Lane Departure Warning ◽

Lane Departure

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A Novel Method for Tramcar Anti-Collision Warning System Based on Monocular Vision

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.430-432.1871 ◽

2012 ◽

Vol 430-432 ◽

pp. 1871-1876

Author(s):

Hui Bo Bi ◽

Xiao Dong Xian ◽

Li Juan Huang

Keyword(s):

Software Design ◽

Early Warning System ◽

Warning System ◽

Detection Algorithm ◽

Lane Detection ◽

Monocular Vision ◽

System Construction ◽

Collision Warning ◽

Lane Width ◽

Novel Method

For the problem of tramcar collision accident in coal mine underground, a monocular vision-based tramcar anti-collision warning system based on ARM and FPGA was designed and implemented. In this paper, we present an improved fast lane detection algorithm based on Hough transform. Besides, a new distance measurement and early-warning system based on the invariance of the lane width is proposed. System construction, hardware architecture and software design are given in detail. The experiment results show that the precision and speed of the system can satisfy the application requirement.

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The Method for Real-Time Length Measurement of Fiber Winding

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.380-384.919 ◽

2013 ◽

Vol 380-384 ◽

pp. 919-922

Author(s):

Chen Xia Guo ◽

Rui Feng Yang

Keyword(s):

Real Time ◽

Detection Algorithm ◽

Moving Target ◽

Fiber Optic Gyroscope ◽

Optical Encoder ◽

The Real ◽

Time Length ◽

Fiber Coil ◽

Fiber Winding ◽

Coil Winding

The paper discusess mainly how to accurately measure the real-time length of fiber optic gyroscope sensing coil (fiber coil) in the process of FOG coil winding. First, using the improved moving target detection algorithm to process the fiber images collected by machine vision. Secondly, using software algorithm to calculate the real-time radius of fiber winding. Finaly, combining the incremental optical encoder with real-time radius to calculate real-time winding length of fiber coil.

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An Optimized Collision Detection Algorithm Based on Dynamic Bounding Volume Tree

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.846-847.1372 ◽

2013 ◽

Vol 846-847 ◽

pp. 1372-1375

Author(s):

Wei Zhao ◽

Li Ming Ye

Keyword(s):

Real Time ◽

Collision Detection ◽

Detection Algorithm ◽

The Real ◽

Bounding Volume

An optimized collision detection algorithm based on dynamic bounding volume tree is proposed in this paper. First this algorithm adopts spatial division to exclude objects which cant intersect to define the potential intersection areas. Then use a new dynamic OBB bounding volume tree to test whether the intersection happened between the objects in the same grid. At last, this algorithm improves the traditional overlapping test between the primitives for accurate collision detection to accelerate the detection between objects. Compared to the traditional collision detection algorithm based on OBB bounding volume. This algorithm can effectively improve the real-time of the collision detection without affecting the accuracy of original collision detection.

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