Representation and retrieval of images using context vectors derived from image information elements
US7072872B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 14, 2004 |
| Grant date | Jul 4, 2006 |
| Priority date | — |
| Expiry date | Jul 31, 2024 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/451
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Image features are generated by performing wavelet transformations at sample points on images stored in electronic form. Multiple wavelet transformations at a point are combined to form an image feature vector. A prototypical set of feature vectors, or atoms, is derived from the set of feature vectors to form an “atomic vocabulary.” The prototypical feature vectors are derived using a vector quantization method, e.g., using neural network self-organization techniques, in which a vector quantization network is also generated. The atomic vocabulary is used to define new images. Meaning is established between atoms in the atomic vocabulary. High-dimensional context vectors are assigned to each atom. The context vectors are then trained as a function of the proximity and co-occurrence of each atom to other atoms in the image. After training, the context vectors associated with the atoms that comprise an image are combined to form a summary vector for the image. Images are retrieved using a number of query methods, e.g., images, image portions, vocabulary atoms, index terms. The user's query is converted into a query context vector. A dot product is calculated between the query vector a…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.