Study on Character Recognition Algorithm for End Faces of Bundled Special Steel Bars
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    Abstract:

    In order to realize the traceability of the whole process of special steel bar production information, the special steel bar production environment and shape characteristics are analyzed. The marking scheme based on double mark points is adopted for marking and the machine vision technology is used to realize the character recognition of the end face of the bundled special steel bars. First, Hough transform is used to segment the end image of the bundle of special steel bars into single ones. Secondly, an image enhancement algorithm based on wavelet transform is used to enhance the end image of a single special steel bar. Then, the MSER algorithm and the edge detection algorithm are combined to complete the detection of the character area of a single special steel bar, and the character segmentation is completed based on the projection method. Finally, the end face character recognition of each special steel bar is completed by creating and training an SVM classifier, and the end face character recognition results of the bundle of special steel bars are output and saved. The special steel bar production environment is simulated in the laboratory and the character recognition algorithm is tested. The results show that the algorithm in this paper can meet the character recognition requirements in the production process of bundled special steel bars, and lay the foundation for the realization of the traceability goal of the whole process of special steel bar production information.

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History
  • Received:June 17,2021
  • Revised:September 27,2021
  • Adopted:October 04,2021
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