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  • Research Article
  • Open Access

Construction of Fisheye Lens Inverse Perspective Mapping Model and Its Applications of Obstacle Detection

EURASIP Journal on Advances in Signal Processing20102010:296598

  • Received: 1 December 2009
  • Accepted: 15 June 2010
  • Published:


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.


  • Warning Signal
  • Source Image
  • Mapping Equation
  • Current Frame
  • Previous Frame

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Authors’ Affiliations

Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, 300, Taiwan
Department of Computer and Communication Engineering, China University of Technology, Hsinchu, 303, Taiwan


© Chin-Teng Lin et al. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.