Method for automatic quantitative statistical distribution characterization of dendrite structures in a full view field of metal materials
US11506650B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 1, 2020 |
| Grant date | Nov 22, 2022 |
| Priority date | — |
| Expiry date | Jul 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30136
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
The invention belongs to the technical field of quantitative statistical distribution analysis for micro-structures of metal materials, and relates to a method for automatic quantitative statistical distribution characterization of dendrite structures in a full view field of metal materials. According to the method based on deep learning in the present invention, dendrite structure feature maps are marked and trained to obtain a corresponding object detection model, so as to carry out automatic identification and marking of dendrite structure centers in a full view field; and in combination with an image processing method, feature parameters in the full view field such as morphology, position, number and spacing of all dendrite structures within a large range are obtained quickly, thereby achieving quantitative statistical distribution characterization of dendrite structures in the metal material. The method is accurate, automatic and efficient, involves a large amount of quantitative statistical distribution information, and is statistically more representative as compared with the traditional measurement of feature sizes of dendrite structures in a single view field.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.