Method and system for splicing and restoring shredded paper based on extreme learning machine
US11132572B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 6, 2019 |
| Grant date | Sep 28, 2021 |
| Priority date | — |
| Expiry date | Sep 6, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/161
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed is a method and system for splicing and restoring shredded paper based on an extreme learning machine (“ELM”). The method includes: acquiring a shredded paper training sample to be spliced; extracting left and right boundary feature data of the sample; training an ELM neural network model according to the feature data to obtain a trained neural network model (“TNNM”); acquiring a shredded paper test sample to be spliced; extracting feature data of the test sample; selecting a first piece of to-be-spliced shredded paper; selecting, by the TNNM, a shredded piece with a highest degree of coincidence with the first piece; determining whether the shredded piece is correctly spliced to the first piece; if yes, splicing shredded paper until all shredded paper is spliced and restored; if not, adopting manual marking, and continuing to select, by the TNNM, shredded paper with a highest degree of coincidence with the first piece.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.