The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 85–91, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-85-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 85–91, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-85-2022
 
30 May 2022
30 May 2022

TRIMMING AND ROAD ORTHO IMAGING FOR NIGHT IMAGES BY ONBOARD HIGH SENSITIVITY CONSUMER GRADE DIGITAL CAMERAS

J. Sugimori1 and H. Chikatsu2 J. Sugimori and H. Chikatsu
  • 1Aero Asahi Corporation, 3501165 Kawagoe Saitama, Japan
  • 2Dept. of Architectural, Civil and Environmental Engineering, Tokyo Denki University, Japan

Keywords: Night Road Ortho-imaging, Quantitative Trimming, Projective Transformation, Onboard High sensitivity Camera

Abstract. Various kinds of cameras have been utilizing as the onboard cameras in the construction of Intelligent Transport Systems. In recent years, utilization of the high sensitivity consumer grade digital cameras at night is attracting attention from the viewpoint of avoiding the effects of sunlight and congestion of people and cars. However, due to the image taken by the onboard cameras is a perspective projection image, the image is projected small at the far from car and the effect of the lens distortion will be greater at points far from the image center. In order to avoid these issues, the lower part of the projection image or a bird's-eye view image is used, but the imaging of the bonnet part caused by the car models and tilts of the cameras becomes a new issue. Furthermore, a bird's-eye view image at night has to be trimmed to coincide with the irradiation range because the irradiation distance and range of the headlights are limited. On the other hand, feature quantities such as vanishing points and feature points on the lane have been used for projective transformation from a perspective projection image to a bird's-eye view image, but the projective transformation based on feature quantities is an ill-posed problem.

Therefore, this paper discusses a quantitative trimming method based on projective transformation that does not depend on feature quantities and coincide with the irradiation range of the headlights.