Line extraction in uncalibrated central images with revolution symmetry

In omnidirectional cameras, straight lines in the scene are projected onto curves called line-images. The shape of these curves is strongly dependent of the particular camera configuration. The great diversity of omnidirectional camera systems makes harder the line-image extraction in a general way. Therefore, it is difficult to design uncalibrated general approaches, and existing methods to extract lines in omnidirectional images require the camera calibration. In this paper, we present a novel method to extract lineimages in uncalibrated images which is valid for radially symmetric central systems. In our proposal, the distortion function is analytically solved for different types of camera systems, dioptric or catadioptric. We present the unified line-image constraints to extract the projection plane of each line and main calibration parameter of the camera from a single line-image. The use of gradient-based information allows computing both from a minimum of two image points. This scheme is used in a line-image extraction algorithm to obtain lines from uncalibrated omnidirectional images without any assumption about the scene. The algorithm is evaluated with synthetic and real images showing good performance.