Persian Optical Character Recognition Using Deep Bidirectional Long Short-Term Memory

Abstract

Optical Character Recognition (OCR) is a system of converting images, including text,into editable text and is applied to various languages such as English, Arabic, and Persian. While these languages have similarities, their fundamental differences can create unique challenges. In Persian, continuity between Characters, the existence of semicircles, dots, oblique, and left-to-right characters such as English words in the context are some of the most important challenges in designing Persian OCR systems. Our proposed framework, Bina, is designed in a special way to address the issue of continuity by utilizing Convolution Neural Network (CNN) and deep bidirectional Long-Short Term Memory (BLSTM), a type of LSTM networks that has access to both past and future context. A huge and diverse dataset, including about 2M samples of both Persian and English contexts,consisting of various fonts and sizes, is also generated to train and test the performance of the proposed model. Various configurations are tested to find the optimal structure of CNN and BLSTM. The results show that Bina successfully outperformed state of the art baseline algorithm by achieving about 96% accuracy in the Persian and 88% accuracy in the Persian and English contexts.

A Survey of OCR in Arabic Language: Applications, Techniques, and Challenges

“…In [11], the authors proposed an Urdu Nastaliq Handwritten Dataset (UNHD), which is written by 500 writers on A4-size paper and is available on request (https://www.kaggle.com/datasets/drsaadbinahmed/ unhd-dataset, accessed on 28 March 2023). Khosrobeigi et al [36] also presented a Persian language dataset; this dataset is collected from different Persian-language new websites, and the description of the dataset is shown in Table 2; this dataset is split into 80% for training and 20% for testing purpose. There are some datasets available that are used for handwritten text recognition of Urdu, and, as we know, Urdu and Arabic use the same vocabulary and alphabet as well.…”