Journal
SENSORS
Volume 20, Issue 20, Pages -Publisher
MDPI
DOI: 10.3390/s20205946
Keywords
pointer meter; deep learning; secondary search; distance method
Funding
- National Key Research and Development Program of China
- Zhejiang Provincial Key Lab of Equipment Electronics
- Fundamental Research Funds for the Provincial Universities of Zhejiang [GK199900299012-026, GK209907299001-001]
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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.
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