This article is written as a complement to the article on good calibration practices recently published on our website. In general, it is very often possible to calibrate the camera system in EikoTwin DIC thanks to the knowledge of the geometry of the part, and of the correspondence between points of the model and images of the structure at rest. In this case, the intrinsic and extrinsic parameters of each of the cameras are initialized simultaneously during pre-calibration. In some cases, in particular when the geometry of the imaged part is very close to that of a plane, it can nevertheless be important to decouple the initialization of the intrinsic and extrinsic parameters of the cameras. In this case, a calibration procedure is used that is called “hybrid”. The intrinsic parameters of each camera are obtained separately from images of calibration charts. In a second step, the extrinsic parameters are determined using the images of the part itself. Both procedures are summarized in Figure 1. To know which procedure is the most adapted to your case, please read the dedicated article ; we focus in this post on hybrid calibration.
In the first part, we will present the test patterns used for the first step of hybrid calibration. In the second part of the article, we will look at the procedure to be followed when taking test pattern images in order to guarantee a good identification of the intrinsic parameters.
(1) As a reminder, the extrinsic parameters of a camera define the position and orientation of the camera in the global reference frame. The intrinsic parameters characterize the camera sensor/lens system (focal length, sensor size, optical center, skew).
Presentation of the ChArUco sights
EikoSim has chosen to use “ChArUco” test charts to perform this hybrid calibration (Figure 2). These test charts differ from conventional checkerboard charts (chessboard type) by the fact that every other square contains a unique ArUco marker, which can be easily detected and identified by image processing algorithms available in the OpenCV library (https://docs.opencv.org/2.4/index.html). In addition to their low purchase cost, the advantage of these charts over conventional checkerboard charts is that each square of the checkerboard, and thus each corner, is uniquely identifiable, allowing image processing even when the checkerboard is not fully visible on the image.
The tests carried out internally at EikoSim have allowed us to define a series of criteria to be respected to ensure that the test pattern images acquired by the user allow a correct determination of the intrinsic parameters sought at this stage:
– Number of images: 20 images per camera are recommended. These images can be acquired synchronously between cameras or not, as the intrinsic parameters are determined independently for each camera. However, it must be ensured that the test patterns appear clearly in the image, as the checkerboard corner detection algorithm may fail if the images are blurred.
– Test pattern size in the image: Ideally, the test pattern should occupy at least 50% of the image size in all cameras. It is recommended to scan the entire volumetric workspace of the camera as described in section 22.214.171.124 of the iDICs guide (link: http://idics.org/guide/DICGoodPracticesGuide_ElectronicVersion-V5g-181022.pdf).
– Variation of test pattern orientations: a variation of 20° along the two axes of the image plane is sufficient to determine the intrinsic parameters with a satisfactory degree of accuracy.
The respect of these criteria is checked in the software when loading the test pattern images into the software.
Processing of test pattern images with EikoTwin DIC 1.2
The import of test pattern images into the software is done after creating a camera by importing the test images in the “Images” tab. In order to be able to load these test pattern images, the user must first specify the reference of the test pattern used for calibration (Figure 3).
A ChAruCo test pattern is entirely defined by six parameters:
- the number of boxes on the checkerboard according to the horizontal and vertical, the width of the boxes (in mm),
- the width of the markers within the boxes (in mm),
- and the number of bits used for each of the markers (number of units).
This data is usually directly visible on the test pattern itself (see Figure 2). Once the test pattern type is filled in, the user can load a folder of images corresponding to this test pattern for each camera. Once these images have been loaded, the software will analyze the test pattern images to determine if they meet the criteria described in the previous paragraph (variation of the test pattern orientation angle on all the images, minimum number of visible corners reached, sufficient size of the test patterns on the image). If these criteria are met, the matrix of intrinsic parameters K returned by the test pattern image processing algorithm will be used for further calibration, during which only the extrinsic parameters will be determined and updated.
The further post-processing in EikoTwin DIC 1.2 (measurement of the shape deviation and calculation of the displacements) remains identical to the current usage from the user’s point of view. You are now ready for a hybrid calibration!