Name
Abstract | ||
|---|---|---|
This paper introduces a project for automatically recognizing ancient Asian characters by image processing and deep learning with the aim of preserving Asian culture. The ancient characters examined include Chinese and Indian characters, which are the most mysterious, wildly used, and historic in the ancient world, and also feature multiply types. The automatic recognition method consists of preprocessing and recognition processing. The preprocessing includes character segmentation and noise reduction, and the recognition processing has a conventional recognition and deep learning. The conventional recognition method consists of feature extraction and similarity calculation or classification, and data augmentation is a key part of the deep learning. Experimental results show that deep learning achieves a better recognition accuracy than conventional image processing. Our aim is to preserve ancient literature by digitizing it and clarifying the characters and how they change throughout history by means of accurate character recognition. We also hope to help people discover new knowledge from ancient literature. |
Year | Venue | Field |
|---|---|---|
2018 | EuroMed | Noise reduction,Pattern recognition,Character recognition,Segmentation,Computer science,Image processing,Feature extraction,Preprocessor,Ancient literature,Artificial intelligence,Deep learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Meng | 1 | 0 | 2.37 |
| C. V. Aravinda | 2 | 0 | 0.34 |
| K. R. Uday Kumar Reddy | 3 | 0 | 0.34 |
| Tomonori Izumi | 4 | 34 | 20.88 |
| Katsuhiro Yamazaki | 5 | 28 | 9.82 |