Hierarchical multiclass exposure defects classification in images
US11494886B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 29, 2020 |
| Grant date | Nov 8, 2022 |
| Priority date | — |
| Expiry date | Nov 4, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30168
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention provide systems, methods, and computer storage media for detecting and classifying an exposure defect in an image using neural networks trained via a limited amount of labeled training images. An image may be applied to a first neural network to determine whether the images includes an exposure defect. Detected defective image may be applied to a second neural network to determine an exposure defect classification for the image. The exposure defect classification can includes severe underexposure, medium underexposure, mild underexposure, mild overexposure, medium overexposure, severe overexposure, and/or the like. The image may be presented to a user along with the exposure defect classification.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.