Browsing by Subject "Camera calibration"
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Item Complementary imaging for pavement cracking measurements(2014-12) Zhao, Zuyun; Xu, BugaoCracking is a major pavement distress that jeopardizes road serviceability and traffic safety. Automated pavement distress survey (APDS) systems have been developed using digital imaging technology to replace human surveys for more timely and accurate inspections. Most APDS systems require special lighting devices to illuminate pavements and prevent shadows of roadside objects that distort cracks in the image. Most of the artificial lighting devices are laser based, which are either hazardous to unprotected people, or require dedicated power supplies on the vehicle. This study is aimed to develop a new imaging system that can scan pavement surface at highway speed and determine the severity level of pavement cracking without using any artificial lighting. The new system consists of dual line-scan cameras that are installed side by side to scan the same pavement area as the vehicle moves. Cameras are controlled with different exposure settings so that both sunlit and shadowed areas can be visible in two separate images. The paired images contain complementary details useful for reconstructing an image in which the shadows are eliminated. This paper intends to presents (1) the design of the dual line-scan camera system for a high-speed pavement imaging system that does not require artificial lighting, (2) a new calibration method for line-scan cameras to rectify and register paired images, which does not need mechanical assistance for dynamical scan, (3) a customized image-fusion algorithm that merges the multi-exposure images into one shadow-free image for crack detection, and (4) the results of the field tests on a selected road over a long period.Item Line scan camera calibration for fabric imaging(2012-05) Zhao, Zuyun; Xu, BugaoFabric defects inspection is a vital step for fabric quality assessment. Many vision-based automatic fabric defect detection methods have been proposed to detect fabric flaws efficiently and accurately. Because the inspection methods are vision-based, image quality is of great importance to the accuracy of detection result. To our knowledge, most of camera lenses have radial distortion. So our goal in this project is to remove the radial distortion and achieve undistorted images. Much research work has been done for 2-D image correction, but the study for 1-D line scan camera image correction is rarely done, although line scan cameras are gaining more and wider applications due to the high resolution and efficiency on 1-D data processing. A novel line scan camera correction method is proposed in this project. We first propose a pattern object with mutually parallel lines and oblique lines to each pair of parallel ones. The purpose of the pattern design is based upon the fact that line scan camera acquires image one line at a time and it's difficult for one scan line to match the "0-D" marked points on pattern. We detect the intersection points between pattern lines and one scan line and calculate their position according to the pattern geometry. As calibrations for 2-D cameras have been greatly achieved, we propose a method to calibrate 1-D camera. A least-square method is applied to solve the pinhole projection equation and estimate the values of camera parameter matrix. Finally we refine the data with maximum-likelihood estimation and get the camera lens distortion coefficients. We re-project the data from the image coordinate to the world coordinate, using the obtained camera matrix and the re-projection error is 0.68 pixel. With the distortion coefficients ready, we correct captured images with an undistortion equation. We introduce a term of unit distance in the discussion part to better assess the proposed method. When testifying the undistortion results, we observe corrected image has almost identical unit distance with standard deviation of 0.29 pixels. Compared to the ideal distortion-free unit distance, the corrected image has only 0.09 pixel off the average, which proves the validity of the proposed method.