Automatic checkerboard detection for camera calibration using self-correlation

Checkerboard Tracker for Camera Calibration

The checkerboard extraction process is an important pre-preprocessing step in camera calibration. This project attempts to implement the checkerboard extraction processes using methods learned from EE368. This includes the isolation of the checkerboard using morphological operations. The benefit of the approach is that it is efficient since morphological operations can be implemented efficientl...

ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration

We present a new checkerboard detection algorithm which is able to detect checkerboards at extreme poses, or checkerboards which are highly distorted due to lens distortion even on low-resolution images. On the detected pattern we apply a surface fitting based subpixel refinement specifically tailored for checkerboard X-junctions. Finally, we investigate how the accuracy of a checkerboard detec...

Fully Automatic Camera Calibration Using Self- Identifying Calibration Targets

Determining camera calibration parameters is an essential step in most computer vision endeavors; it is a time-consuming task despite the availability of calibration algorithms and software. A set of point correspondences between points on the calibration target and the camera image(s) must be found, usually a manual or manually guided process. Two commonly used calibration tools are implementa...

A checkerboard detection utility for intrinsic and extrinsic camera cluster calibration

Automatic Chessboard Detection for Intrinsic and Extrinsic Camera Parameter Calibration

There are increasing applications that require precise calibration of cameras to perform accurate measurements on objects located within images, and an automatic algorithm would reduce this time consuming calibration procedure. The method proposed in this article uses a pattern similar to that of a chess board, which is found automatically in each image, when no information regarding the number...