## 1 Introduction  
In the process of managing the life cycle of an existing structure or developing a new type of structure, it is important to directly measure the kinetic and kinematic variables such as stress and strain of the structural member, or accurately estimate them through an analytical method. In practice, the deformation or strain of a specimen is directly obtained via linear variable differential transformers (LVDT) or strain gauges, or using numerical simulations such as meshfree methods [1, 2]. Since obtaining all the kinematic variables at the desired location through direct measurement is uneconomical and time-intensive, it is more efficient to measure a few variables directly and use them to numerically estimate the other variables. Recently, an alternative method for deriving the kinematic variables of multiple test specimens or large-scale experiments was developed by combining a mechanical test and a numerical simulation method [3]. In particular, with the advancements in computing performance and the reduction of computational cost, methods to supplement or partially replace mechanical tests using digital image processing (DIP) have been studied [4; 5; 6; 7]. In the field of structural experiments using DIP, digital images can be analyzed and processed to obtain useful information related to structural analysis. Moreover, the experimental limitations of DIP such as the number or location of measurement points can be overcome by combining DIP with numerical analysis methods. This combination allows, for example, the extraction of the required number of mechanical variables from a desired location using a limited amount of direct measurement information when the number or scale of the target structure is large. [PERSON] et al. [8] demonstrated the usefulness of image-based methods by comparing the vibration measurement results of the finite element method (FEM) with those of digital image correlation, dynamic photogrammetry, laser, and acceleration measurement equipment. This technique is used to evaluate the condition of structures such as in mechanical tests or structural health monitoring, where crack detection is important [9; 10]. Digital image correlation estimates the deformation of a specimen by tracking a specific point by analyzing the correlation of the speckle patterns in the images obtained before and after the deformation of the specimen, based on mechanical tests mainly used for small specimens. [PERSON] and [PERSON] [11] used this technique to measure the mode I crack propagation in reinforced concrete structures. [PERSON] et al. [12] used this technique to measure the deflection of aluminum specimens. [PERSON] et al. [13] suggested a technology to measure the displacement and vibration of rock columns by using digital image correlation and analyzed its applicability through field tests. Similarly, digital image correlation is applied to various material technologies; however, the accuracy of this technique varies with the speckle pattern of the images used for the correlation analysis [14]. The conventional Newton-Raphson algorithm is difficult to apply in digital image correlation if a large deformation or rotation is present. This technique is time-consuming because it requires numerous calculations based on the reconstruction of repetitive subsets [15]. While DIC has high accuracy, an additional algorithm such as the Newton-Raphson method is required for efficient analysis. This algorithm needs complicated analysis due to differential calculation and requires high computation cost. Therefore, in this study, we applied the DIP method to track the displacement of a target attached to a specimen directly from the image. This eliminates the need for a speckle pattern or a subset for displacement tracking. In this study, a simple algorithm that directly tracks the target was proposed using DIP.