A New Approach to the Generation of Orthoimages of Cultural Heritage Objects—Integrating TLS and Image Data

Abstract

This paper discusses the issue of automation of orthoimage generation based on Terrestrial Laser Scanning (TLS) data and digital images. The following two problems are discussed: automatic generation of projection planes based on TLS data, and automatic orientation of digital images in relation to TLS data. The majority of popular software applications use manual definitions of projection planes. However, the authors propose an original software tool to address the first issue, which defines important planes based on a TLS point cloud utilizing different algorithms (RANdom SAmple Consensus-RANSAC, Hough transform, "region growing"). To address the second task, the authors present a series of algorithms for automated digital image orientation in relation to a point cloud. This is important in cases where scans and images are acquired from different places and at different times. The algorithms utilize Scale Invariant Feature Transform(SIFT) operators in order to find points that correspond in reflectance intensity between coloure images (Red Green Blue-RGB) and orthoimages, based on TLS data. The paper also presents a verification method using SIFT and Speeded-Up Robust Features (SURF) operators. The research results in an original tool and applied Computer Vision(CV) algorithms that improve the process of orthoimage generation.

The Influence of the Cartographic Transformation of TLS Data on the Quality of the Automatic Registration

“…The main disadvantage of the method is related to difficulties in detection and interpolation of planes used to generate the DSM. Detailed descriptions and comparisons of different algorithms for detection of planes are presented in publications on computer vision and photogrammetry [43][44][45] The advantage of using cartographic projections to represent the point cloud is the possibility of considering deformations in the process of raster data generation. The Mercator projection allows for projection of the upper fragments of scans with smaller geometric deformations.…”

“…Table 1 presents the average time of TLS data conversion for particular cartographic projections and test site in minutes and seconds. For planes detection, the Hough 2D method were used [44]. It can be seen from Table 1 that the shortest time for data conversion into the raster form is obtained in the case of the spherical images and the longest time in the case of the orthoimage (Test site III).…”

“…It can be seen from Table 1 that the shortest time for data conversion into the raster form is obtained in the case of the spherical images and the longest time in the case of the orthoimage (Test site III). The time of processing TLS data to the orthoimages depends on the number of detected planes and it is an influence on the complexity of the process of computations [44].…”

Integration of Point Clouds From Terrestrial Laser Scanning and Image-Based Matching for Generating High-Resolution Orthoimages

“…In the first step, a reference plane was determined, which served as the basis for generation of the Digital Surface Model (Markiewicz et al, 2015) in the GRID structure. The nearest-neighbour interpolation algorithm was used for this purpose.…”

“…The use of close-range photogrammetry for works related to cultural heritage still needs further research. The main research strand aiming to optimize modelling of historical objects focuses on the integration of data collected by means of several measuring technologies (Guarnieri et al, 2006;Ramos, et al, 2015;Markiewicz, Zawieska, 2014;Markiewicz et al 2015). Combining of data from terrestrial laser scanning and image matching is increasingly being used to improve the quality of products (Baptista, 2013).…”