A study on idiosyncratic handwriting with impact on writer identification

Publication Type:
Conference Proceeding
Citation:
Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR, 2018, 2018-August pp. 193 - 198
Issue Date:
2018-12-05
Filename Description Size
conference_041818 (1).pdfAccepted Manuscript version337.92 kB
Adobe PDF
Full metadata record
© 2018 IEEE. In this paper, we study handwriting idiosyncrasy in terms of its structural eccentricity. In this study, our approach is to find idiosyncratic handwritten text components and model the idiosyncrasy analysis task as a machine learning problem supervised by human cognition. We employ the Inception network for this purpose. The experiments are performed on two publicly available databases and an in-house database of Bengali offline handwritten samples. On these samples, subjective opinion scores of handwriting idiosyncrasy are collected from handwriting experts. We have analyzed the handwriting idiosyncrasy on this corpus which comprises the perceptive ground-truth opinion. We also investigate the effect of idiosyncratic text on writer identification by using the SqueezeNet. The performance of our system is promising.
Please use this identifier to cite or link to this item: