Pardal Cardama, XaimeRegueiro, Carlos V.Rodríguez Luaces, Miguel2026-09-152026-09-152025Pardal Cardama, X., Regueiro, C. V., & Luaces, M. R. (2026). Real-time Defect Detection in Conveyor Belts using Point Clouds Generated by a ToF Camera. In Proceedings XoveTIC 2025: Impulsando el talento científico (pp. 249-256). Servizo de Publicacións UDC. https://doi.org/10.17979/spu.23.c42978-84-9749-925-5https://hdl.handle.net/2183/49255Presentado en: VIII Congreso Xove TIC: impulsando el talento científico. Octubre, 2025, A Coruña.[Abstract] A three-dimensional analysis system was developed using Time-of-Flight (ToF) infrared cameras to detect conveyor belt teeth and estimate their speed. From the captured point clouds, structural patterns are identified through geometric fitting and spatial segmentation. As a novel contribution, the system detects belt teeth, locating absences and deformations. Detection is performed by comparing the expected distribution with the observed one. The speed of the conveyor belt is estimated by calculating the relative displacement between consecutive point clouds. The system was successfully tested, providing accurate and reliable analysis in dynamic industrial environments.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Conveyor belt inspectionTime-of-Flight (ToF) imagingPoint cloud processingDefect detectionIndustrial automationconference outputopen access10.17979/spu.23.c42