Least-squares method and deep learning in the identification and analysis of name-plates of power equipment
Publié en ligne: 15 déc. 2021
Pages: 103 - 112
Reçu: 16 juin 2021
Accepté: 24 sept. 2021
© 2021 Yerong Zhong et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Comparison of experimental results based on the SVT dataset
Method |
F-value, % |
Sundararajan et al. [1] |
53.00 |
Yang et al. [2] |
64.00 |
O’Brien et al. [3] |
66.18 |
CTPN + CRNN |
64.34 |
CTPN + OCR software |
42.50 |
This study |
68.69 |
Comparison of nameplate recognition accuracy
Method |
OCR software |
Sundararajan et al. [1] |
CTPN + CRNN |
Yang et al. [2] |
This study |
Accuracy, % |
67.1 |
82.7 |
82.34 |
84.11 |
87.71 |
Partial image processing time
Size |
Number of characters/piece |
Detection time, s |
Recognition time, s |
Total time, s |
301 × 472 |
31 |
0.341 |
2.76 |
3.101 |
300 × 401 |
70 |
0.289 |
2.1 |
2.389 |
450 × 800 |
83 |
0.364 |
2.25 |
2.614 |
532 × 710 |
73 |
0.141 |
2.81 |
2.951 |
241 × 629 |
78 |
0.321 |
2.66 |
2.981 |
3024 × 4032 |
63 |
0.542 |
2.12 |
2.662 |