A robust algorithm for reading recognition of pointer instrument with local matching

Tun Niu; Liang Ye

doi:10.1117/12.2692930

7 March 2024 A robust algorithm for reading recognition of pointer instrument with local matching

Tun Niu, Liang Ye

Proceedings Volume 13088, MIPPR 2023: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 130880H (2024) https://doi.org/10.1117/12.2692930
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China

Abstract

The inspection and recognition of readings on pointer instruments are important tasks in power inspection. Due to the diversity and the complex dial information of pointer instruments, the adaptability and low accuracy of existing methods are not enough. In this paper, we proposed a pointer instrument reading recognition algorithm based on local fast matching. Firstly, YOLOv8 is used to locate and segment the instrument in the inspection image. The positions and values of key scale are marked in the template image. Based on the key local information, a mapping relationship is established between the instrument location region in the inspection image and the template image. Then, the Hough transform is used to detect the position of the pointer, map it to the template image, and finally calculate the instrument reading based on the relative positions of the key graduations on the template image and the mapped pointer position. Experimental results demonstrate that the proposed method achieves a relative error within 5% for pointer instrument reading recognition in indoor substations.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tun Niu and Liang Ye "A robust algorithm for reading recognition of pointer instrument with local matching", Proc. SPIE 13088, MIPPR 2023: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 130880H (7 March 2024); https://doi.org/10.1117/12.2692930

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KEYWORDS

Equipment

Image segmentation

Inspection

Detection and tracking algorithms

Matrices

Hough transforms

Image processing

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