Takaaki Iizuka

Improving light marker accuracy on camera images

The accuracy of measurement systems that use image processing is very dependent on the method used to determine the target center position on the image. The digital image correlation (DIC) method,1 which combines image matching and sub-pixel estimation using correlation interpolation, enables registration of pairs of images in many processing applications, such as camera calibration and measurement of structures or fluids. However, DIC is unable to determine the exact center position. Therefore, a light marker is installed on the surface of the object and the central point of the marker is estimated by the centroid calculation method (where the geometric center is determined).2 Although this method can be realized with the sub-pixel accuracy of DIC, there is a bias error in the measurement, depending on the threshold that separates the bright spot from the region of interest.3 Our study proposes a dynamic threshold method to reduce the bias and error of the calculated value. In addition, we evaluated the measurement accuracy of the center position of a bright spot and analyzed the error in certain imaging conditions using Monte Carlo simulation. We sought to improve the well-known technique of threshold selection for image binarization (converting to a black and white image) known as discriminant analysis.4, 5 This technique selects an optimal threshold by the discriminant criterion, which maximizes the separability of two classes in a gray-level histogram. The sub-pixel position measurement has a systematic error when used with this threshold selection method, which is caused by a higher threshold compared with the average intensity of the background (see Figure 1). Our study proposes an improved dynamic threshold method from discriminant analysis by using a threshold fth D m1 C k 1, where m1 and 1 are the average and variance, respectively, of the gray level of the background (denoted as class 1 in Figure 1) and k is a coefficient. This equation indicates that the threshold varies depending on Figure 1. Gray-level histogram of a light-marker image. The dotted line indicates the threshold value selected by the discriminant analysis method. Class 1 and class 2 denote background and object, respectively.

Real Time Displacement Measurement of Lattice Pattern Using High Speed Camera

The 2D or 3D displacement measurement is required in the vibration testing for the scenic technology because of the complex loading conditions. However, there is no convenient 2D displacement measurement. In this research, 2D displacement measurement with real time image processing is developed. The target of camera image is a lattice pattern drawn on the paper sheet.