A Modified Back Propagation Algorithm for Assyrian Optical Character Recognition Based on Moments | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 34, 2B, February 2016, Pages 255-268 PDF (921 K) | ||
| DOI: 10.30684/etj.34.2B.8 | ||
| Authors | ||
| Luma Fayeq Jalil; Modhar Mohsen Mohammed | ||
| Abstract | ||
| Character recognition has been very popular and interested area for researches, and it continues to be a challenging and impressive research topic due to its diverse applicable environment. The optical character recognition has been introduced as a fast and accurate method to convert both existing text images as well as large archives of existing paper documents to editable digital text format. However, existing optical character recognition algorithms suffer from flawed tradeoffs between accuracy and speed, making them less effective and impractical for large and complex documents. This paper describes a suggested method for Assyrian optical character recognition using modified back propagation artificial neural network based on moments. The experimental results show that the proposed method achieves higher recognition accuracy rate in compared with the standard algorithm. | ||
| Keywords | ||
| OCR; Assyrian characters; Segmentation; feature extraction; Classification; Training; Back Propagation Neural Network Algorithm | ||
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