# Experimental Validation of Non-Marker Simple Image Displacement Measurements for Railway Bridges
## 2 Related Contributions  
Due to advancements in cost and video capability, such as the development of high speeds and high resolutions, image measuring using a video camera is gradually becoming more common. Because railway bridge displacement is the primary structural index, in this section previous major contributions are reviewed, with a particular emphasis on bridge displacement measurements and application instances using images. The method of measuring bridge displacement using images and markers is long standing. [PERSON] and [PERSON] [10] reported the measurement of actual bridges using industrial video cameras in 2006. Subsequently, numerous improvements and applications of bridge displacement measurement methods have been made using industrial video cameras. For example, [PERSON] et al. [11] proposed a method of measuring bridge dynamic displacement using a handheld video recorder via an image processing method that resizes the region of interest and updates the coefficients. [PERSON] et al. [12] established a displacement measurement system for railway bridges using an industrial video camera. They proposed a method using a dedicated marker to track a similar position in the image obtained by digital image correlation (DIC). Moreover, lights and windshields were employed to ensure adequate illumination and limit the camera's instability. In video measurement in which accuracy is a problem, their method achieved a relatively high accuracy of 0.1 mm (shooting from a 10 m point). [PERSON] et al. [13] examined the effects of the camera type, image processing techniques, and magnification levels on image-based methods of measuring bridge displacement during train passage. They noted that a significant increase in measurement error is unavoidable in non-marker displacement measurements. [PERSON] et al. established a displacement measurement system for railway bridges through several studies using industrial video cameras [14; 15; 16]. Moreover, the accuracy was empirically verified, not only when using markers, but also when measuring the displacement without markers [16]. They proposed a sub-pixel estimation method for high-resolution displacement measurement [15]. [PERSON] et al. proposed a DIC-based image displacement measurement system for railway bridges [17]. Here, a computer-controlled industrial video camera was proposed for use in non-marker deflection measurements and a real-time system that allows the results to be confirmed at the measurement site. Furthermore, several active studies and contributions related to image displacement measurements are underway, as detailed in two review papers [18; 19]. [PERSON] and [PERSON] (2018) summarized the importance of multipoint measurement data obtained from imagesfrom the damage detection perspective [18]. Moreover, [PERSON] and [PERSON] (2018) discussed the use of structural health monitoring and the difficulties that should be addressed in the future for each elemental technology (camera calibration, target tracking, and structural displacement calculation) [19]. Recently, [PERSON] et al. [20] realized a remote image measurement method using aerial vehicles. The automation and simplification of imaging using aerial vehicles and robots have significant potential to simplify the patrol and inspection of structures, which is the premise of this study. Although the use of aerial vehicles is an important research subject, it is outside the scope of this study and a future's task. Several of the aforementioned studies confirmed their measurements on actual bridges after sufficient confirmation of their accuracy in the laboratory. Therefore, there are few instances in which the scope of application is discussed after understanding the limits of the camera distance and the measurable environmental conditions, in terms of both measurable and unmeasurable data. However, the quantification of the relationship between the camera distance and the measurement accuracy performed by [PERSON] et al. [12] is a remarkable contribution.