Comparative Accuracy Assessment of Point Cloud Registration Methods in Terrestrial Laser Scanning: A Case Study of a Mosque Façade
Keywords:
Terrestrial laser scanning, Point cloud registration, Iterative Closest Point, Accuracy assessment, Geomatics engineering.Abstract
Point-cloud registration, the alignment of multiple overlapping terrestrial laser scanning (TLS) stations into a single coordinate system, is the most error-sensitive stage of the TLS workflow, since any residual misalignment propagates into every derived product. Quantitative comparisons of different registration strategies on the same real-world dataset remain scarce, particularly for architecturally complex façades. This paper compares four registration strategies available in commercial TLS software (Cloud-to-Cloud, Target-Based, Top-View, and a combined Topview-and-Cloud-to-Cloud approach) together with a target-based manual refinement, using the same cleaned eight-station scan of a university mosque façade acquired with a FARO Focus 3D X330 scanner. Each strategy is evaluated by mean point-position accuracy and inter-scan overlap. Among the automatic strategies, the combined Topview-and-Cloud-to-Cloud method gave the lowest maximum error (±11.6 mm) and the Top-View method the largest (±32.9 mm). The target-based manual refinement outperformed all automatic strategies, reducing the mean point error to ±4.1 mm and raising the minimum overlap to 16.5%. The results show that high overlap alone does not guarantee geometric accuracy, and that target-based manual registration remains the most reliable strategy for detailed façades.
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