Real-time Defect Detection in Conveyor Belts using Point Clouds Generated by a ToF Camera
| UDC.coleccion | Publicacións UDC | |
| UDC.conferenceTitle | XoveTIC: impulsando el talento científico (8º. 2025. A Coruña) | |
| UDC.departamento | Enxeñaría de Computadores | |
| UDC.departamento | Ciencias da Computación e Tecnoloxías da Información | |
| UDC.endPage | 256 | |
| UDC.grupoInv | Grupo de Arquitectura de Computadores (GAC) | |
| UDC.grupoInv | Laboratorio de Bases de Datos (LBD) | |
| UDC.institutoCentro | CITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación | |
| UDC.startPage | 249 | |
| dc.contributor.author | Pardal Cardama, Xaime | |
| dc.contributor.author | Regueiro, Carlos V. | |
| dc.contributor.author | Rodríguez Luaces, Miguel | |
| dc.date.accessioned | 2026-09-15T17:31:54Z | |
| dc.date.available | 2026-09-15T17:31:54Z | |
| dc.date.issued | 2025 | |
| dc.description | Presentado en: VIII Congreso Xove TIC: impulsando el talento científico. Octubre, 2025, A Coruña. | |
| dc.description.abstract | [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. | |
| dc.identifier.citation | Pardal 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.c42 | |
| dc.identifier.doi | 10.17979/spu.23.c42 | |
| dc.identifier.isbn | 978-84-9749-925-5 | |
| dc.identifier.uri | https://hdl.handle.net/2183/49255 | |
| dc.language.iso | eng | |
| dc.publisher | Universidade da Coruña, Servizo de Publicacións | |
| dc.relation.uri | https://doi.org/10.17979/spu.23.c42 | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Conveyor belt inspection | |
| dc.subject | Time-of-Flight (ToF) imaging | |
| dc.subject | Point cloud processing | |
| dc.subject | Defect detection | |
| dc.subject | Industrial automation | |
| dc.title | Real-time Defect Detection in Conveyor Belts using Point Clouds Generated by a ToF Camera | |
| dc.type | conference output | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | f87255cd-0609-4002-a032-d84ffa367c00 | |
| relation.isAuthorOfPublication | fbde3bd9-d786-4ef0-89ec-6af2091fa415 | |
| relation.isAuthorOfPublication.latestForDiscovery | f87255cd-0609-4002-a032-d84ffa367c00 |
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