• Infrared and Laser Engineering
  • Vol. 51, Issue 12, 20220102 (2022)
Xun Zhang, Jinxiong Zhao, Wanrong Bai, and Hong Zhao
Author Affiliations
  • Electric Power Research Institute of State Grid Gansu Electric Power Company, Lanzhou 730000, China
  • show less
    DOI: 10.3788/IRLA20220102 Cite this Article
    Xun Zhang, Jinxiong Zhao, Wanrong Bai, Hong Zhao. Research on optical character recognition algorithm based on boundary constrained image fusion[J]. Infrared and Laser Engineering, 2022, 51(12): 20220102 Copy Citation Text show less

    Abstract

    In order to improve the recognition ability of optical characters in non-cooperative target areas, and enhance the accuracy of information collection such as power nameplates and power grid texts, an optical character recognition system was designed that simultaneously collected polarized images and visible light images and performed image fusion. By setting the polarization angles of 0°, 60° and 120°, the response voltage was periodically modulated to obtain the connectivity range of the effective information region and achieve accurate boundary constraints. By calculating the polarization angle calibration parameters and setting reasonable thresholds of boundary conditions, a range standard was provided for image fusion. The function curves of the response voltage on the polarization angle and the test distance were tested in the experiment, and the results showed that the slope of the periodic change of the polarization angle was 53.1 mV/(°). In the range of 0.5-3.0 m, the maximum value of the response voltage was 241.7 mV, the minimum voltage was 18.5 mV, and the monotonicity of the three response curves was almost the same. The experiment was carried out on the power nameplate target with poor image definition. The results showed that after traditional image filtering and enhancement, the contrast ratio of the blurred original image was increased from 0.34 to 1.56, and the image quality was improved to a certain extent, but there were still some characters that could not be identified. After using this algorithm, the contrast ratio reaches 3.23, and some fuzzy characters can also be effectively recognized. It can be seen that the system is suitable for optical character recognition of non-cooperative targets, and has a good optimization effect on optical character recognition in low-quality images.
    Xun Zhang, Jinxiong Zhao, Wanrong Bai, Hong Zhao. Research on optical character recognition algorithm based on boundary constrained image fusion[J]. Infrared and Laser Engineering, 2022, 51(12): 20220102
    Download Citation