Name
Abstract | ||
|---|---|---|
For extracting information from the historical documents, digitization efforts have increased dramatically in the recent decades. Accurate layout analysis will help researchers for developing more robust HTR and OCR techniques which will extract meaningful information from these documents. Variable layouts, low quality and distorted images of historical documents create different problems to deal with when compared to modern document processing. Arabic script features have even more problems for these automatic processing systems. In this study, we have developed a tool for automatically analyzing the layouts of the first Ottoman population registers which are written in Arabic script form. We built a dataset for testing the performance of our system which are chosen from the first population records of the Ottoman Empire between the 1840s and 1860s. We successfully classified two different object types in those documents. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/SIU49456.2020.9302464 | 2020 28th Signal Processing and Communications Applications Conference (SIU) |
Keywords | DocType | ISSN |
page segmentation,historical document analysis,convolutional neural networks,Arabic layout analysis | Conference | 2165-0608 |
ISBN | Citations | PageRank |
978-1-7281-7207-1 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yekta Said Can | 1 | 0 | 1.01 |
| M. Erdem Kabadayi | 2 | 0 | 0.34 |