Automatic detection of object pixels for hyperspectral analysis
US8965060B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 9, 2012 |
| Grant date | Feb 24, 2015 |
| Priority date | — |
| Expiry date | Jan 12, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/68
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method is provided for automatically discerning between object and non-object pixels in a hyperspectral image data cube. In particular embodiments, the object of the method is a plant, plant part, plant trait, plant phenotype, plant pot or a plant medium. The method comprises a first step of providing a partial least squares discriminant analysis (PLSDA) algorithm and a second step of applying the PLSDA algorithm to a hyperspectral image data cube to automatically determine which pixels contain the spectral properties of the object. The PLSDA algorithm of the method can be generated by establishing a training matrix, performing an eigenvector decomposition of the training matrix, experimentally determining a weighted linear combination of object signal-containing eigenvectors, calculating a regression vector using the weighted linear combination of signal-containing eigenvectors, generating a mask matrix and multiplying the mask matrix by the hyperspectral image data cube along two spatial dimensions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.