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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yousefi, M.R. Soheili, M.R. Breuel, T.M. Kabir, E. Stricker, D. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Tarbiat Modares Univ., Tehran, Iran (Kabir, E.) || Tech. Univ. of Kaiserslautern, Kaiserslautern, Germany (Breuel, T.M.) || German Res. Center for Artificial Intell. (DFKI), Kaiserslautern, Germany (Yousefi, M.R.; Soheili, M.R.; Stricker, D.) |
| Abstract | A primary preprocessing block of almost any typical OCR system is binarization, through which it is intended to remove unwanted part of the input image, and only keep a binarized and cleaned-up version for further processing. The binarization step does not, however, always perform perfectly, and it can happen that binarization artifacts result in important information loss, by for instance breaking or deforming character shapes. In historical documents, due to a more dominant presence of noise and other sources of degradations, the performance of binarization methods usually deteriorates; as a result the performance of the recognition pipeline is hindered by such preprocessing phases. In this paper, we propose to skip the binarization step by directly training a 1D Long Short Term Memory (LSTM) network on gray-level text lines. We collect a large set of historical Fraktur documents, from publicly available online sources, and form train and test sets for performing experiments on both gray-level and binarized text lines. In order to observe the impact of resolution, the experiments are carried out on two identical sets of low and high resolutions. Overall, using gray-level text lines, the 1D LSTM network can reach 24% and 19% lower error rates on the low- and high-resolution sets, respectively, compared to the case of using binarization in the recognition pipeline. |
| Starting Page | 1121 |
| Ending Page | 1125 |
| File Size | 1053476 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479918058 |
| DOI | 10.1109/ICDAR.2015.7333935 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-23 |
| Publisher Place | Tunisia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Degradation Image resolution Libraries Text analysis Irrigation Jacobian matrices |
| Content Type | Text |
| Resource Type | Article |
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