Method and system for unsupervised word image clustering
US10095957B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 14, 2017 |
| Grant date | Oct 9, 2018 |
| Priority date | — |
| Expiry date | Feb 14, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/762
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present application provides a method and system for unsupervised word image clustering, comprises capturing one or more image wherein the one or more image comprises at least one word images. Extracting at least one feature vector using an untrained convolution neural network architecture, wherein the convolution filters are initialized by random filter based deep learning techniques using Gaussian random variable with zero mean and unit standard deviation, and wherein the convolution filters are constrained to sum to zero. The extracted feature vectors are used for clustering, wherein clustering is performed in two stages. First stage includes clustering word images which are similar using a graph connected component. Second stage clustering includes clustering a remaining word images which are not clustered during the first stage by evaluating the remaining images against the clusters formed during the first stage and assigning them to clusters based on the evaluation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.