2010/03/30 by Sandip Rakshit, Rakshit, Sandip, Amitava Kundu +9 · 3 citations
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Image Processing and 3D Reconstruction #Image and Object Detection Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.1003.5898
Proc. Int. Conf. on Advances in Computer Vision and Information Technology (2009) 572-577
arxiv created 2010/03/30 · openalex publication_date 2010/03/30 · arxiv updated 2010/03/31 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
The objective of the paper is to recognize handwritten samples of Roman numerals using Tesseract open source Optical Character Recognition (OCR) engine. Tesseract is trained with data samples of different persons to generate one user-independent language model, representing the handwritten Roman digit-set. The system is trained with 1226 digit samples collected form the different users. The performance is tested on two different datasets, one consisting of samples collected from the known users (those who prepared the training data samples) and the other consisting of handwritten data samples of unknown users. The overall recognition accuracy is obtained as 92.1% and 86.59% on these test datasets respectively.