Representation and retrieval of images using context vectors derived from image information elements
US6173275A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Sep 17, 1997 |
| Grant date | Jan 9, 2001 |
| Priority date | — |
| Expiry date | Sep 17, 2017 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S706/934
- 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 …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.