Image analysis through neural network using image average color
US8428348B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 15, 2009 |
| Grant date | Apr 23, 2013 |
| Priority date | — |
| Expiry date | Feb 20, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/7715
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Architecture for comparing images by building an initial map from the average color and an inserted blackened area. Accordingly, a map can be built that is more information-rich and smaller, thereby making the system more efficient. The architecture employs a Kohonen neural network (or self-organizing map (SOM)) by guiding the learning of the SOM using characteristics of the images such as average color and a central area. A strong component of the average color of the image and the central area at the approximate center of the image are added to the uninitialized SOM, which allows related colors to converge toward the central area of the image. When input, the SOM organizes the color content of the image on a map, which can be used to compare the image with other images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.