Accuracy Improvement by Artificial Neural Networks in Technical Vision System
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
This paper proposes an Artificial Neural Network (ANN) to accurately predict the real angles obtained by a Triangulation Vision System. The performance of the ANN is compared with the K-Nearest Neighbors algorithm from previous publications. For the experimentation it was necessary to create a database to train and prove both methods in different coordinates on a determinate area through the dynamic triangulation method. Afterwards, the root mean square error is calculated to obtain the accuracy of each algorithm. Finally, several laser scanning measurements were taken at different distances to analyze the measurement dispersion of both algorithms.
| Original language | English |
|---|---|
| Title of host publication | IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society |
| Number of pages | 6 |
| Place of Publication | Piscataway |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Publication date | 10.2019 |
| Pages | 5572-5577 |
| Article number | 8927596 |
| ISBN (print) | 978-1-7281-4879-3 |
| ISBN (electronic) | 978-1-7281-4878-6 |
| DOIs | |
| Publication status | Published - 10.2019 |
| Event | 45th Annual Conference of the Institute of Electrical and Electronics Engineers' Industrial Electronics Society - 2019 - Lisbon Congress Center, Lisbon, Portugal Duration: 14.10.2019 → 17.10.2019 Conference number: 45 https://iecon2019.org/ |
- Engineering
- Artificial Neural Networks, dynamic triangulation, K-Nearest Neighbors, laser scanning