Národní úložiště šedé literatury Nalezeno 1 záznamů.  Hledání trvalo 0.01 vteřin. 
Automatic Tire Inspection Using Surface Scans
Toth Vaňo, Pavol ; Materna, Zdeněk (oponent) ; Španěl, Michal (vedoucí práce)
This thesis deals with automatic detection of defects on tire treads using their depth scans. The approach proposed in the thesis doesn’t require a faultless reference tire for the inspected tire. The first step is the detection of anomalies, which is done using a modification of the PatchCore method proposed in the thesis, taking advantage of the repetition of patterns on the tire tread. Subsequently, anomalies corresponding to special elements on the tire are detected using the deep neural networks Faster R-CNN and Deep Hough transform, and they are filtered out. Applying the proposed approach on the prepared dataset, the value 0.584 of Average Precision metric for detection was obtained. The biggest weakness of the proposed method is its limited ability to detect defects with a very small depth.

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