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A Method of Image Identification in Instrumentation

  • Wang, Xiaoli (School of Mechanical, Electrical and Information Engineering, Shandong University) ;
  • Wang, Shilin (School of Mechanical, Electrical and Information Engineering, Shandong University) ;
  • Jiang, Baochen (School of Mechanical, Electrical and Information Engineering, Shandong University)
  • Received : 2018.01.30
  • Accepted : 2018.03.15
  • Published : 2018.06.30

Abstract

Smart city is currently the main direction of development. The automatic management of instrumentation is one task of the smart city. Because there are a lot of old instrumentation in the city that cannot be replaced promptly, how to makes low-cost transformation with Internet of Thing (IoT) becomes a problem. This article gives a low-cost method that can identify code wheel instrument information. This method can effectively identify the information of image as the digital information. Because this method does not require a lot of memory or complicated calculation, it can be deployed on a cheap microcontroller unit (MCU) with low read-only memory (ROM). At the end of this article, test result is given. Using this method to modify the old instrumentation can achieve the automatic management of instrumentation and can help build a smart city.

Keywords

References

  1. A. Vishnuvarthanan, M. P. Rajasekaran, V. Govinadaraj, Y. Zhang, and A. Thiyagarajan, "Development of a combinational framework to concurrently perform tissue segmentation and tumor identification in T1-W, T2-W, FLAIR and MPR type magnetic resonance brain images," Expert Systems with Applications, vol. 95, pp. 280-311, 2018. https://doi.org/10.1016/j.eswa.2017.11.040
  2. T. Go, H. Byeon, and S. J. Lee, "Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning," Biosensors and Bioelectronics, vol. 103, pp. 12-18, 2018. https://doi.org/10.1016/j.bios.2017.12.020
  3. X. Ma, M. Tian, J. Zhang, L. Tang, and F. Liu, "Flow pattern identification for two-phase flow in a U-bend and its contiguous straight tubes," Experimental Thermal and Fluid Science, vol. 93, pp. 218-234, 2018. https://doi.org/10.1016/j.expthermflusci.2017.12.024
  4. H. Z. M, Shah, M. Sulaiman, A. Z. Shukor, Z. Kamis, and A. Ab Rahman, "Butt welding joints recognition and location identification by using local thresholding," Robotics and Computer-Integrated Manufacturing, vol. 51, pp. 181-188, 2018. https://doi.org/10.1016/j.rcim.2017.12.007
  5. Q. Zhao, F. Sun, W. Li, and P. Liu, "Flame detection using generic color model and improved block-based PCA in active infrared camera," International Journal of Pattern Recognition and Artificial Intelligence, vol. 32, no. 5, article no. 1850014, 2018.
  6. Z. Liu, S. Wang, and M. Zhang, "Improved sparse 3D transform-domain collaborative filter for screen content image denoising," International Journal of Pattern Recognition and Artificial Intelligence, vol. 32, no. 3, article no. 1854006, 2018.
  7. L. Lambert, G. Grusova, A. Buraetova, P. Matras, A. Lambertova, and P. Kuchynaka, "The predictive value of computed tomography in the detection of reflux esophagitis in patients undergoing upper endoscopy," Clinical Imaging, vol. 49, pp. 97-100, 2018. https://doi.org/10.1016/j.clinimag.2017.11.009