A robust and automatic recognition system of analog instruments in power system by using computer vision. (October 2016)

• Record Type: Journal Article
• Authors: Zheng, Chao; Wang, Shaorong; Zhang, Yihan; Zhang, Pengxiang; Zhao, Yong
• Is Part Of: Measurement. Volume 92(2016)
• Page Start: 413
• Page End: 420
• Publication Date: 2016-10
• Subjects: Analog instrument -- Automatic recognition system -- Computer vision -- Multi-Scale Retinex with color restoration -- Perspective Transform -- Hough Transform; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2016.06.045
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: The MSRCR is employed to eliminate the influence of brightness. The Perspective Transform is applied to calibrate the camera angle of images. The proposed recognition system can read analog instruments in Power System. Abstract: It is a puzzling issue found in the field of Supervisory Control and Data Acquisition (SCADA) to read automatically the indication of analog measuring instruments, which collects many states of power system equipment. To address this problem, a lot of approaches based on computer vision have been proposed for the automatic reading of the analog measuring instruments indication. However, most the proposed systems are sensitive to brightness. Moreover, since the camera angle must be vertical, the robustness of the approaches cannot meet application requirements. In this paper, the proposed recognition system uses a novel automatic reading approach, which can automatically read the indication of analog measuring instruments at various brightness levels and camera angles. It is an integrated application of Multi-Scale Retinex with color restoration at different brightness levels, Perspective Transform to get the front view of image taken from arbitrary camera angle, and Hough Transform to determine the pointer position. The test results verify the good robustness of the recognition system to the brightness and camera angle.