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- W2980265321 abstract "Can end rivet fracture is considered a serious defect that may arise during the manufacturing of metal cans used in food industry. Its occurrence may result in inefficiency of the easy-opening system, leakage or contamination of the food. Thus, an inspection procedure must be performed in order to remove the defective can ends from the production line. However, the location of the rivet and the characteristics of the fracture defect make it difficult to use simple devices for online inspection of 100% of the cans. In this paper, a new method for detecting fracture defects in can end rivets based on machine vision is described. In the proposed technique the rivets are detected employing Otsu segmentation, morphological filtering and connected component analysis. The classification of each rivet as being defective or non defective is performed using a minimum distance classifier based on circularity and area features. The software and hardware architecture of a real time inspection system and the technical aspects for its integration into a production line are presented. The described system can achieve an accuracy as high as 98.13% for rivet defects detection according to experiments and tests performed in real conditions of use." @default.
- W2980265321 created "2019-10-18" @default.
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- W2980265321 date "2019-10-01" @default.
- W2980265321 modified "2023-10-02" @default.
- W2980265321 title "A Machine Vision System for Online Metal Can-End Rivet Inspection" @default.
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- W2980265321 doi "https://doi.org/10.1088/1742-6596/1335/1/012002" @default.
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