NDLI: Robust hypothesis generation method using binary blob analysis for multi-lane detection

Content Provider	IET Digital Library
Author	Piao, Jingchun Shin, Hyunchul
Abstract	The vision-based lane detection is an important component of advanced driver assistance systems and it is essential for lane departure warning, lane keeping, and vehicle localisation. However, it is a challenging problem to improve the robustness of multi-lane detection due to factors, such as perspective effect, possible low visibility of lanes, and partial occlusions. To deal with these issues, the authors propose an improved lane hypothesis generation method using a reliable binary blob analysis. Most existing top-view based methods focused on the lane model fitting, but they neglected the reliability of hypothesis generation and the effectiveness in challenging conditions. To cope with these shortcomings, the authors carried out vanishing point detection and inverse perspective mapping to remove the perspective effect from the road images. Then two-stage binary blob filtering and blob verification techniques using classification are introduced to improve the robustness of lane hypothesis generation for lane detection. The experimental results show that the average detection accuracy on a new challenging multi-lane dataset is 97.7%. The performance of the proposed method outperforms that of the state-of-the-art method by 1.6% in detection accuracy on the Caltech lane benchmark dataset.
Starting Page	1210
Ending Page	1218
Page Count	9
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 12, Dec (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0506
Journal	IET Image Processing
Publisher Date	2017-08-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Advanced Driver Assistance System Computer Vision Computer Vision And Image Processing Technique Driver Information System Filtering Method in Signal Processing Image Classification Image Filtering Image Recognition Improved Lane Hypothesis Generation Method Inverse Perspective Mapping Lane Departure Warning Lane Keeping Multilane Dataset Multilane Detection Object Detection Partial Occlusions Perspective Effect Possible Low Visibility-of-lanes Reliable Binary Blob Analysis Road Traffic Robust Hypothesis Generation Method Traffic Engineering Computing Two-stage Binary Blob Filtering Technique Two-stage Binary Blob Verification Technique Vanishing Point Detection Vehicle Localisation Vision-based Lane Detection
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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