Method for separating out a defect image from a thermogram sequence based on feature extraction and multi-objective optimization
US10846841B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2019 |
| Grant date | Nov 24, 2020 |
| Priority date | — |
| Expiry date | May 27, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30168
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention provides a method for separating out a defect image from a thermogram sequence based on feature extraction and multi-objective optimization, we find that different kinds of TTRs have big differences in some physical quantities, such as the energy, temperature change rate during endothermic process, temperature change rate during endothermic process, average temperature, maximum temperature. The present invention extract these features (physical quantities) and cluster the selected TTRs into L clusters based on their feature vectors, which deeply digs the physical meanings contained in each TTR, makes the clustering more rational, and improves the accuracy of defect separation. Meanwhile, the present invention creates a multi-objective function to select a RTTR for each cluster based on multi-objective optimization. The multi-objective function does not only fully consider the similarities between the RTTR and other TTRs in the same cluster, but also considers the dissimilarities between the RTTR and the TTRs in other clusters, the RTTR is more representative, which guarantees the accuracy of describing the defect outline.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.