Abstract
This paper focuses on the calibration problem using stereo camera images. Currently, advanced vehicle systems such as smart cars and mobile robots require accurate and reliable vision in order to detect obstacles and special marks around. Such modern vehicles can be equipped with sensors and cameras together or separately. In this study, we propose new methodologies of stereo camera calibration based on the correction of distortion and image rectification. Once the calibration is complete, the validation of the corrections is presented followed by an evaluation of the calibration process. Usually, the validation section is not jointly considered with the calibration in other studies. However, the mass production of cameras widely uses the validation techniques in calibrations owned by manufacturing businesses. Here, we aim to present a single process for the calibration and validation of stereo cameras. The experiment results showed the disparity maps in comparison with another study and proved that the proposed calibration methods can be efficient.
Highlights
IntroductionMany sensors are being utilized in vehicles to reduce or lighten collision accidents
Calibration using a stereo camera was carried by extracting vertex of squares, regarding a checkerboard composed of white and black squares
Since there is no verification method for the current camera calibration algorithm, it was utilized under the assumption that the calibration was performed well
Summary
Many sensors are being utilized in vehicles to reduce or lighten collision accidents. RADAR, single camera, and stereo camera sensors, in particular, are individually occupied or infused to avoid a forward collision. Camera sensors are often applied to detect pedestrians, cars, traffic lights, signs, and other obstacles in the same way as drivers on a road [1,2,3]. It is preferred that a stereo camera distinguishes obstacles with
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