Robust Real-Time Lane Detection in Luminance Variation Using Morphological Processing

“Real-Time Lane Detection for Driving System Using Image Processing”

In the past decade a lot of research has been done on vision based real-time advanced driver safety system (ADAS). Many OEM car manufacturing companies have stressed their research on ADAS so as to increase the vehicle and driver safety. This work is aimed at developing an algorithm for on road lane departure warning (LDW) system. LDW can be successfully used for dropping the on road accidents ...

Building A Robust, Real-Time Vision-Based Lane Detection Algorithm

Robust Real-Time Lane Delimiting Features Extraction

This paper presents a robust lane marking detection algorithm suited for a large variety of traffic scenarios, under various lighting conditions. The algorithm detects dark-light-dark transitions using an improved method for horizontal gradient computation, which accounts for the expected marking width and for the perspective effect by means of a variable size filter. The computation of the var...

Robust Real-Time Lane and Road Detection in Critical Shadow Conditions

This paper presents the vision-based road detection system currently installed onto the MOB-LAB land vehicle. Based on a geometrical transform and on a fast morphological processing, the system is capable to detect road markings even in extremely severe shadow conditions on at and structured roads. The use of a special-purpose massively architecture (PAPRICA) allows to achieve a processing rate...

Real-time Lane Detection for Driving System Using Image Processing Based on Edge Detection and Hough Transform

Real-time Lane Detection for Driving System Using Image Processing Based on Edge Detection and Hough Transform has been developed to aid a driver in the lane departure decision-making, to reduce a loss of concentration and to prevent an accident while driving. In this paper, we propose a method for detecting the lane markers in real time by using a webcam camera to record the road as a video st...