Image segmentation using hierarchical unsupervised segmentation and hierarchical classifiers
US8873812B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 6, 2012 |
| Grant date | Oct 28, 2014 |
| Priority date | — |
| Expiry date | Jan 23, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20076
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An image segmentation method includes generating a hierarchy of regions by unsupervised segmentation of an input image. Each region is described with a respective region feature vector representative of the region. Hierarchical structures are identified, each including a parent region and its respective child regions in the hierarchy. Each hierarchical structure is described with a respective hierarchical feature vector that is based on the region feature vectors of the respective parent and child regions. The hierarchical structures are classified according to a set of predefined classes with a hierarchical classifier component that is trained with hierarchical feature vectors of hierarchical structures of training images. The training images have semantic regions labeled according to the set of predefined classes. The input image is segmented into a plurality of semantic regions based on the classification of the hierarchical structures and optionally also on classification of the individual regions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.