Bibliographic Details
| Title: |
NVIDIA TX2-Based Inkjet Character Detection Algorithm. (English) |
| Authors: |
LI Fan, HU Weiping, LIU Beibei, LIU Yuge |
| Source: |
Journal of Computer Engineering & Applications; Jul2022, Vol. 58 Issue 13, p210-216, 7p |
| Subject Terms: |
Text recognition, Pattern recognition systems, Algorithms, Food packaging, Food processing plants |
| Abstract: |
Aiming at the phenomenon of spray leakage, re-spray, deficiency of inkjet characters under the background of complex commodities, an inkjet character detection algorithm based on YOLOv5 + CRNN is proposed. The inkjet character positioning algorithm is based on YOLOv5, combined with the attention mechanism to improve its detection accuracy. Then, the number and complexity of model parameters are reduced through sparse training and channel pruning, so that the final detection accuracy is increased by 3.4 percentage points, and the amount of model parameters is reduced by 6.7 MB. After erasing background and perspective transformation, the positioned character area is send to the CRNN network to complete the recognition of inkjet character. Finally, the improved algorithm is deployed to the NVIDIA TX2 embedded platform. Through the actual measurement in the production lines of the food packaging factory, the testing speed of the model reaches 28 frame/s, the accuracy of character-localization is 99.4%, and the recognition rate is 95% with good robustness. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |