Lane detection and kalman-based linear-parabolic lane tracking

This paper presents a lane detection and linear-parabolic lane tracking system using kalman filtering method. First, the image horizon is detected in a traffic scene to split the sky and road region. Road region is further analyzed with entropy method to remove the road pixels. Lane boundaries are t...

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Main Authors: Lim, Hann, Seng, K., Ang, L., Chin, S.
Format: Conference Paper
Published: 2009
Online Access:http://hdl.handle.net/20.500.11937/32955
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author Lim, Hann
Seng, K.
Ang, L.
Chin, S.
author_facet Lim, Hann
Seng, K.
Ang, L.
Chin, S.
author_sort Lim, Hann
building Curtin Institutional Repository
collection Online Access
description This paper presents a lane detection and linear-parabolic lane tracking system using kalman filtering method. First, the image horizon is detected in a traffic scene to split the sky and road region. Road region is further analyzed with entropy method to remove the road pixels. Lane boundaries are then extracted from the region using lane markings detection. These detected boundaries are tracked in consecutive video frames with a linear-parabolic tracking model. The model parameters are updated with Kalman filtering method. Error-checking is performed iteratively to ensure the performance of the lane estimation model. Simulation results demonstrate good performance of the proposed Kalman-based linear-parabolic lane tracking system with fine parameters update. © 2009 IEEE.
first_indexed 2025-11-14T08:30:26Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:30:26Z
publishDate 2009
recordtype eprints
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spelling curtin-20.500.11937-329552017-09-13T15:27:13Z Lane detection and kalman-based linear-parabolic lane tracking Lim, Hann Seng, K. Ang, L. Chin, S. This paper presents a lane detection and linear-parabolic lane tracking system using kalman filtering method. First, the image horizon is detected in a traffic scene to split the sky and road region. Road region is further analyzed with entropy method to remove the road pixels. Lane boundaries are then extracted from the region using lane markings detection. These detected boundaries are tracked in consecutive video frames with a linear-parabolic tracking model. The model parameters are updated with Kalman filtering method. Error-checking is performed iteratively to ensure the performance of the lane estimation model. Simulation results demonstrate good performance of the proposed Kalman-based linear-parabolic lane tracking system with fine parameters update. © 2009 IEEE. 2009 Conference Paper http://hdl.handle.net/20.500.11937/32955 10.1109/IHMSC.2009.211 restricted
spellingShingle Lim, Hann
Seng, K.
Ang, L.
Chin, S.
Lane detection and kalman-based linear-parabolic lane tracking
title Lane detection and kalman-based linear-parabolic lane tracking
title_full Lane detection and kalman-based linear-parabolic lane tracking
title_fullStr Lane detection and kalman-based linear-parabolic lane tracking
title_full_unstemmed Lane detection and kalman-based linear-parabolic lane tracking
title_short Lane detection and kalman-based linear-parabolic lane tracking
title_sort lane detection and kalman-based linear-parabolic lane tracking
url http://hdl.handle.net/20.500.11937/32955