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

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.

Mobile Robot Navigation Techniques Using Potential Field Method in Unknown Environments

“…In order to compute the distance from the camera to a forward vehicle, the authors of [12,16] transform the forward facing image to a top-down "bird's eye" view, in which there is a linear relationship between distances in the image and in the real world. More than that, in [13] the authors develop an Inverse Perspective Mapping Model that is used to map in 3D all the obstacles around a vehicle. The depth into an image was also done by using algorithms for depth estimating from a single still image depending on texture variations and gradients, defocus, color/haze [14].…”