Automatic writer identification using connected-component contours and edge-based features of uppercase western script

作者：Schomaker L^*; Bulacu M

来源：IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(6): 787-798.

DOI：10.1109/TPAMI.2004.18

• writer identification
• connected-component contours
• edge-orientation features
• stochastic allograph emission model

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 PDF) of CO(3)s was computed for an independent test set containing 150 unseen writers. Results revealed a high-sensitivity of the CO3 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 CO3 PDF with an independent edge-based orientation and curvature PDF yielded very high correct identification rates.

• 出版日期2004-6