Two-dimensional (2-D) Kalman Segmentation Approach in Mobile Laser Scanning (MLS) Data for Panoramic Image Registration

Abstract

Currently, as a result of the massive continuous advancements in laser technology, possibilities of map production are broadened, the loss of time and the waste of material sources are highly prevented, and the accuracy and precision of the obtained results are significantly improved. In this study an automated survey (building facade survey) is produced from mobile scanning data for the purpose of examining the benefits and disadvantages of mobile laser measurement systems compared to conventional measurement systems by looking at their characteristics and application areas. In turn, a two-dimensional (2-D) Kalman filtering algorithm and a related laser data segmentation method are developed in order to acquire ortho-photo (rectified) images from the facade images for computer-aided design (CAD) survey. Specific window corner points of the building are automatically detected and the results are analysed in order to combine the data by implementing them into a sample mobile laser data set.