Method for identifying handwritten characters on an image using a classification model
US12327422B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 28, 2022 |
| Grant date | Jun 10, 2025 |
| Priority date | — |
| Expiry date | Jan 18, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q40/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for identifying handwritten characters on an image using a classification model that employs a neural network. The system includes a computer having a processor and a memory device that stores data and executable code that, when executed, causes the processor to read and convert typed text on the image to machine encoded text to identify locations of the typed text on the image; identify a location on the image that includes handwritten text based on the location of predetermined typed text on the image; identify clusters of non-white pixels in the image at the location having the handwritten text, where constraints are employed to refine and limit the clusters; generate an individual and separate cluster image for each identified cluster; and classify each cluster image using machine learning and at least one neural network to determine the likelihood that the cluster is a certain character.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.