Scalable Imaging Device using Line Scan Camera for Use in Biometric Recognition and Medical Imaging

Detection and Identification of Expansion Joint Gap of Road Bridges by Machine Learning Using Line-Scan Camera Images

“…This system uses the geographical information system data of the bridge (above, longitude coordinate system) to perform automatic measurements in conjunction with the mounted GPS while driving at high speed and thereby creates a database of the expansion gaps based on accurate survey images without affecting the traffic flow. In this study, a test survey was conducted on approximately 5000 bridges along the highway, and the analysis results were used for big-data-based machine learning for developing algorithms to accurately determine the length of the expansion joint gap depending on its type and site conditions (see Figure 3) [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62]. The NEXUS system and the on-site test survey introduction is available on our YouTube channel [63].…”

“…Second, semantic segmentation is the process of classifying each pixel in an image belonging to a particular class. The recent success of CNN has also driven outstanding progress in semantic segmentation [37][38][39][40][41][42][43][44][45][46]. Based on CNN architecture, the semantic segmentation model extracts local contexts (a small area centered in a pixel to classify) and global contexts (overall semantics of input image) from an image and reconstructs contexts to create a class heatmap of the same size as the original image, which shows the probability of which class each pixel is.…”