Research on Character Recognition Technology of Long Material Surface Identification
Aiming at the difficulties of conventional scene text recognition methods,such as the mark characters on the surface of long products often located on the surface in the industrial environment,and the lack of training samples,this paper proposes a recognition strategy for the characters on the surface of long products in the industrial environment.Firstly,the two-dimensional image is transformed into a binary image suitable for the detection algorithm through the adaptive hybrid threshold binarization algorithm,and the character location algorithm based on DBNet semantic segmentation and its corresponding post-processing algorithm are used to locate and correct the located region,and then the single character segmentation recognition method is used to complete the recognition.Finally,the method proposed in this paper is compared and verified.The results show that the targeted improvement proposed in this paper for each link of long products surface character recognition has achieved a certain improvement in the recognition accuracy index and intuitive effect compared with the existing methods,and has a certain engineering application feasibility.
long products surface markhybrid threshold binarizationsingle character recognition
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