Szczegóły publikacji

Opis bibliograficzny

Inclusion detection in injection-molded parts with the use of edge masking / Paweł ROTTER, Maciej KLEMIATO, Dawid KNAPIK, Maciej ROSÓŁ, Grzegorz Putynkowski // Sensors [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1424-8220. — 2024 — vol. 24 iss. 22 art. no. 7150, s. 1–18. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 17–18, Abstr. — Publikacja dostępna online od: 2024-11-07

Autorzy (5)

Słowa kluczowe

defect detectionimage matchingobject classificationoptical inspection

Dane bibliometryczne

ID BaDAP156866
Data dodania do BaDAP2025-01-13
Tekst źródłowyURL
DOI10.3390/s24227150
Rok publikacji2024
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaSensors

Abstract

The algorithm and prototype presented in the article are part of a quality control system for plastic objects coming from injection-molding machines. Some objects contain a flaw called inclusion, which is usually observed as a local discoloration and disqualifies the object. The objects have complex, irregular geometry with many edges. This makes inclusion detection difficult, because local changes in the image at inclusions are much less significant than grayscale changes at the edges. In order to exclude edges from calculations, the presented method first classifies the object and then matches it with the corresponding mask of edges, which is prepared off-line and stored in the database. Inclusions are detected based on the analysis of local variations in the surface grayscale in the unmasked part of the image under inspection. Experiments were performed on real objects rejected from production by human quality controllers. The proposed approach allows tuning the algorithm to achieve very high sensitivity without false detections at edges. Based on input from the controllers, the algorithm was tuned to detect all the inclusions. At 100% recall, 87% precision was achieved, which is acceptable for industrial applications.

Publikacje, które mogą Cię zainteresować

artykuł
#143182Data dodania: 2.11.2022
Monitoring subsidence area with the use of satellite radar images and deep transfer learning / Anna FRANCZYK, Justyna BAŁA, Maciej DWORNIK // Sensors [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1424-8220. — 2022 — vol. 22 iss. 20 art. no. 7931, s. 1–14. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 12–14, Abstr. — Publikacja dostępna online od: 2022-10-18
fragment książki
#156181Data dodania: 20.11.2024
Efficient object detection in fused visual and infrared spectra for edge platforms / Piotr Janyst, Bogusław CYGANEK, Łukasz Przebinda // W: Data Analytics in System Engineering : proceedings of 7th Computational Methods in Systems and Software 2023, Vol. 4. — Cham : Springer, cop. 2024. — (Lecture Notes in Networks and Systems ; ISSN 2367-3370 ; vol. 935). — ISBN: 978-3-031-54819-2; e-ISBN: 978-3-031-54820-8. — eds. Radek Silhavy, Petr Silhavy. — S. 243–253. — Bibliogr., Abstr. — B. Cyganek - dod. afiliacja: MyLED Inc., Kraków