Abstract
Existing reading recognition methods of the pointer type meter have problems of inaccurate target segmentation, high manual dependence of dial detection and low accuracy. This paper presents a self-tuning parameter pointer type meter reading recognition based Gamma correction. In detail, the proposed approach firstly processes the image by Gamma correction with the contrast to output the high contrast image. Then the presented method makes the circle Hough transform by automatically adjusting the parameter to segment the dial. Next, the algorithm further processes image by OTSU, refinement and Hough line transform to segment image and extract pointer. Finally, it calculates the slope of the detected line, and combines the lookup method with the formula method to interpret the indicator. Experimental results show that the proposed method can realize the automatic detection of the dial and accurate segmentation of the pointer, and the obtained reading is more close to the actual reading. The algorithm is more stable and reliable.
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Acknowledgements
This work is supported partly by National Natural Science Foundation of China under Grant No. 61703373, Doctor Fund Project of Zhengzhou University of Light Industry under Grant No. 13501050026.
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Liu, Y., Shi, K., Zhang, Z., Hu, Z., Liu, A. (2020). A Stable and Reliable Self-tuning Pointer Type Meter Reading Recognition Based on Gamma Correction. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_297
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DOI: https://doi.org/10.1007/978-981-13-9409-6_297
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