Laser & Optoelectronics Progress, Volume. 59, Issue 24, 2410001(2022)
Fully Automatic Reading Recognition for Pointer Meters Based on Lightweight Image Semantic Segmentation Model
Fig. 1. Flow chart of proposed method
Fig. 2. Network structure of modified image semantic segmentation model
Fig. 3. Gaussian heat map label generation
Fig. 4. Sematic segmentation results and separated binary images. (a) Semantic segmentation results; (b) binary image of scale lines; (c) binary image of pointer; (d) binary image of scale-range numbers
Fig. 5. Correction for skew and distorted image. (a) Dial ellipse fitting result; (b) schematic graph of perspective transformation
Fig. 6. Image correction and denoising results. (a) Scale line; (b) pointer; (c) scale-range numbers
Fig. 7. Image polar transform. (a) Polar coordinate transform coordinate system; (b) polar coordinate transform result
Fig. 8. Location and repair of scale lines and pointer. (a) Contour refinement result; (b) center line positioning result; (c) scale line repair result
Fig. 9. Comparison of semantic segmentation effects for different lightweight models
Fig. 10. Gray images (left) and binary images (right) of scale-range numbers
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Fuhai Yan, Wangming Xu, Qiugan Huang, Shiqian Wu. Fully Automatic Reading Recognition for Pointer Meters Based on Lightweight Image Semantic Segmentation Model[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2410001
Category: Image Processing
Received: Sep. 1, 2021
Accepted: Oct. 27, 2021
Published Online: Jan. 11, 2023
The Author Email: Xu Wangming (xuwangming@wust.edu.cn)