Training text recognition systems
US10997463B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2018 |
| Grant date | May 4, 2021 |
| Priority date | — |
| Expiry date | Jun 23, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In implementations of recognizing text in images, text recognition systems are trained using noisy images that have nuisance factors applied, and corresponding clean images (e.g., without nuisance factors). Clean images serve as supervision at both feature and pixel levels, so that text recognition systems are trained to be feature invariant (e.g., by requiring features extracted from a noisy image to match features extracted from a clean image), and feature complete (e.g., by requiring that features extracted from a noisy image be sufficient to generate a clean image). Accordingly, text recognition systems generalize to text not included in training images, and are robust to nuisance factors. Furthermore, since clean images are provided as supervision at feature and pixel levels, training requires fewer training images than text recognition systems that are not trained with a supervisory clean image, thus saving time and resources.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.