A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection
Automatic reading of pointer meters is of great significance for efficient measurement of industrial meters. However, existing algorithms are defective in the accuracy and robustness to illumination shooting angle when detecting various pointer meters. Hence, a novel algorithm for adaptive detection...
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2020-10-01
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Online Access: | https://www.mdpi.com/1424-8220/20/20/5946 |
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doaj-a6c8c118ecd04d6799a55015b8bdef5d2020-11-25T03:36:10ZengMDPI AGSensors1424-82202020-10-01205946594610.3390/s20205946A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text DetectionZhu Li0Yisha Zhou1Qinghua Sheng2Kunjian Chen3Jian Huang4School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310000, ChinaSchool of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310000, ChinaSchool of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310000, ChinaSchool of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310000, ChinaSchool of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310000, ChinaAutomatic reading of pointer meters is of great significance for efficient measurement of industrial meters. However, existing algorithms are defective in the accuracy and robustness to illumination shooting angle when detecting various pointer meters. Hence, a novel algorithm for adaptive detection of different pointer meters was presented. Above all, deep learning was introduced to detect and recognize scale value text in the meter dial. Then, the image was rectified and meter center was determined based on text coordinate. Next, the circular arc scale region was transformed into a linear scale region by polar transform, and the horizontal positions of pointer and scale line were obtained based on secondary search in the expanded graph. Finally, the distance method was used to read the scale region where the pointer is located. Test results showed that the algorithm proposed in this paper has higher accuracy and robustness in detecting different types of meters.https://www.mdpi.com/1424-8220/20/20/5946pointer meterdeep learningsecondary searchdistance method |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhu Li Yisha Zhou Qinghua Sheng Kunjian Chen Jian Huang |
spellingShingle |
Zhu Li Yisha Zhou Qinghua Sheng Kunjian Chen Jian Huang A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection Sensors pointer meter deep learning secondary search distance method |
author_facet |
Zhu Li Yisha Zhou Qinghua Sheng Kunjian Chen Jian Huang |
author_sort |
Zhu Li |
title |
A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection |
title_short |
A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection |
title_full |
A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection |
title_fullStr |
A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection |
title_full_unstemmed |
A High-Robust Automatic Reading Algorithm of Pointer Meters Based on Text Detection |
title_sort |
high-robust automatic reading algorithm of pointer meters based on text detection |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-10-01 |
description |
Automatic reading of pointer meters is of great significance for efficient measurement of industrial meters. However, existing algorithms are defective in the accuracy and robustness to illumination shooting angle when detecting various pointer meters. Hence, a novel algorithm for adaptive detection of different pointer meters was presented. Above all, deep learning was introduced to detect and recognize scale value text in the meter dial. Then, the image was rectified and meter center was determined based on text coordinate. Next, the circular arc scale region was transformed into a linear scale region by polar transform, and the horizontal positions of pointer and scale line were obtained based on secondary search in the expanded graph. Finally, the distance method was used to read the scale region where the pointer is located. Test results showed that the algorithm proposed in this paper has higher accuracy and robustness in detecting different types of meters. |
topic |
pointer meter deep learning secondary search distance method |
url |
https://www.mdpi.com/1424-8220/20/20/5946 |
work_keys_str_mv |
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