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Construction of fisheye lens inverse perspective mapping model and its applications of obstacle detection

Authors:

Yu-Wen ShouAuthors Info & Claims

EURASIP Journal on Advances in Signal Processing, Volume 2010

Article No.: 8, Pages 1 - 23

https://doi.org/10.1155/2010/296598

Published: 01 February 2010 Publication History

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Abstract

In this paper, we develop a vision based obstacle detection system by utilizing our proposed fisheye lens inverse perspective mapping (FLIPM) method. The new mapping equations are derived to transform the images captured by the fisheye lens camera into the undistorted remapped ones under practical circumstances. In the obstacle detection, we make use of the features of vertical edges on objects from remapped images to indicate the relative positions of obstacles. The static information of remapped images in the current frame is referred to determining the features of source images in the searching stage from either the profile or temporal IPM difference image. The profile image can be acquired by several processes such as sharpening, edge detection, morphological operation, and modified thinning algorithms on the remapped image. The temporal IPM difference image can be obtained by a spatial shift on the remapped image in the previous frame. Moreover, the polar histogram and its post-processing procedures will be used to indicate the position and length of feature vectors and to remove noises as well. Our obstacle detection can give drivers the warning signals within a limited distance from nearby vehicles while the detected obstacles are even with the quasi-vertical edges.

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Cited By

Cadiz LHernandez A(2019)Hybrid Detection for Vehicle Blind Spot using Fisheye CameraProceedings of the 2019 5th International Conference on Computing and Artificial Intelligence10.1145/3330482.3330524(250-253)Online publication date: 19-Apr-2019
https://dl.acm.org/doi/10.1145/3330482.3330524
Subudhi BGhosh SCho SGhosh A(2016)Integration of fuzzy Markov random field and local information for separation of moving objects and shadowsInformation Sciences: an International Journal10.1016/j.ins.2015.10.031331:C(15-31)Online publication date: 20-Feb-2016
https://dl.acm.org/doi/10.1016/j.ins.2015.10.031

Index Terms

Construction of fisheye lens inverse perspective mapping model and its applications of obstacle detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
  2. Machine learning
    1. Machine learning approaches
2. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems

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Information & Contributors

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Published In

cover image EURASIP Journal on Advances in Signal Processing

EURASIP Journal on Advances in Signal Processing Volume 2010, Issue

Special issue on advanced image processing for defense and security applications

February 2010

575 pages

ISSN:1110-8657

Issue’s Table of Contents

Publisher

Hindawi Limited

London, United Kingdom

Publication History

Accepted: 15 June 2010

Revised: 15 April 2010

Published: 01 February 2010

Received: 01 December 2009

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Cited By

Cadiz LHernandez A(2019)Hybrid Detection for Vehicle Blind Spot using Fisheye CameraProceedings of the 2019 5th International Conference on Computing and Artificial Intelligence10.1145/3330482.3330524(250-253)Online publication date: 19-Apr-2019
https://dl.acm.org/doi/10.1145/3330482.3330524
Subudhi BGhosh SCho SGhosh A(2016)Integration of fuzzy Markov random field and local information for separation of moving objects and shadowsInformation Sciences: an International Journal10.1016/j.ins.2015.10.031331:C(15-31)Online publication date: 20-Feb-2016
https://dl.acm.org/doi/10.1016/j.ins.2015.10.031

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