Automatic writer identification using connected-component contours and edge-based features of uppercase western scriptSchomaker, L. & Bulacu, M., Jun-2004, In : Ieee transactions on pattern analysis and machine intelligence. 26, 6, p. 787-798 12 p.
Research output: Contribution to journal › Article › Academic › peer-review
In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO(3)s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected components for the uppercase character set. Using a codebook of CO(3)s from an independent training set of 100 writers, the probability-density function (PDF) of CO(3)s was computed for an independent test set containing 150 unseen writers. Results revealed a high-sensitivity of the CO(3) PDF for identifying individual writers on the basis of a single sentence of uppercase characters. The proposed automatic approach bridges the gap between image-statistics approaches on one end and manually measured allograph features of individual characters on the other end. Combining the CO(3) PDF with an independent edge-based orientation and curvature PDF yielded very high correct identification rates.
|Number of pages||12|
|Journal||Ieee transactions on pattern analysis and machine intelligence|
|Publication status||Published - Jun-2004|
- writer identification, connected-component contours, edge-orientation features, stochastic allograph emission model, RECOGNITION, ONLINE, SKILL
Firemaker image collection for benchmarking forensic writer identification using image-based pattern recognition
Schomaker, L. (Creator), Vuurpijl, L. (Creator), University of Groningen, 1-Jan-2000