TY - GEN
T1 - Automatic Analog Pointer Instruments Reading Using Panel Detection and Landmark Localization Networks
AU - Yang, Keshan
AU - Duan, Zhansheng
AU - Fang, Kai
N1 - Publisher Copyright:
© 2019, Springer Nature Singapore Pte Ltd.
PY - 2019
Y1 - 2019
N2 - Analog pointer instruments are widely used in industrial automation. However, reading their values by human is time and labour consuming. Most current pointer reading algorithms lack universality and can not handle complex and varying application scenarios. Therefore, this paper proposes a general pointer instrument reading scheme based on CNN. Our main contributions are two folds. First, we combine two sub-networks into one backbone, which has shortened the inference time. Second, we propose a light-weighted sampling decoder, which makes our scheme achieve a higher accuracy. Comparing to other algorithms, our scheme can deal with the case in which the instrument is too difficult to read, e.g., there is more than one similar pointer in one panel. Also, our scheme only needs less than 100Â ms on a typical laptop for a 512 × 512 image. It is fast enough and can satisfy most requirements in industrial automation.
AB - Analog pointer instruments are widely used in industrial automation. However, reading their values by human is time and labour consuming. Most current pointer reading algorithms lack universality and can not handle complex and varying application scenarios. Therefore, this paper proposes a general pointer instrument reading scheme based on CNN. Our main contributions are two folds. First, we combine two sub-networks into one backbone, which has shortened the inference time. Second, we propose a light-weighted sampling decoder, which makes our scheme achieve a higher accuracy. Comparing to other algorithms, our scheme can deal with the case in which the instrument is too difficult to read, e.g., there is more than one similar pointer in one panel. Also, our scheme only needs less than 100Â ms on a typical laptop for a 512 × 512 image. It is fast enough and can satisfy most requirements in industrial automation.
KW - Landmark localization
KW - Panel detection
KW - Pointer instrument reading
UR - https://www.scopus.com/pages/publications/85065775676
U2 - 10.1007/978-981-13-7983-3_1
DO - 10.1007/978-981-13-7983-3_1
M3 - 会议稿件
AN - SCOPUS:85065775676
SN - 9789811379826
T3 - Communications in Computer and Information Science
SP - 3
EP - 14
BT - Cognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers
A2 - Sun, Fuchun
A2 - Hu, Dewen
A2 - Liu, Huaping
PB - Springer Verlag
T2 - 4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018
Y2 - 29 November 2018 through 1 December 2018
ER -