Abstract
Currently, there are numerous methods for detecting product defects by combining deep learning and machine vision, which are the core technologies of the fourth industrial revolution. In this study, we have developed a software that can identify defects, based on deep learning and machine vision, using the Keras open source library. The software was used to determine the defect based on an image of the regular product, and then identify its location using probability distribution. In addition, three verification experiments were carried out, the first which is a basic verification experiment, using an image produced by an image editor, the second, using an assembly block; and finally, a semi-real application experiment using an electric bread-board. Through these experiments, it was confirmed that machine vision-based defect detection system using deep learning algorithm could idetify the defects and pinpoint their locations.
| Translated title of the contribution | Machine Vision-based Defect Detection Using Deep Learning Algorithm |
|---|---|
| Original language | Korean |
| Pages (from-to) | 47-52 |
| Number of pages | 6 |
| Journal | 비파괴검사학회지 |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2020 |