Machine learning models for direct homography regression for image rectification
US11481683B1 · kind B1 · utility
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20Claims
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Key dates
| Filing date | May 29, 2020 |
| Grant date | Oct 25, 2022 |
| Priority date | — |
| Expiry date | Apr 17, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0464
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for creating machine learning models for direct homography regression for image rectification are described. In certain embodiments, a training service trains an algorithm on a source view of a training image and a homography matrix of the training image into a machine learning model that generates a normalized homography matrix for an input of the source view. The normalized homography matrix may then be utilized to generate a target view of an image input into the machine learning model. The target view of the image may be used in a document processing pipeline for document images captured using cameras.
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