Raw material form recognition based on Tesseract-OCR
Haodong Fang, Min Bao · 2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS) · 2021
For bearing companies, there are still many handwritten forms in the inspection of raw materials at present, and raw material data is also related to the traceability of finished products, which will inevitably affect the progress of the entire production process and product quality. Based on OCR technology and Tesseract-OCR character recognition foundation, this paper designs a set of raw material inspection form intelligent recognition and matching system. After performing denoising and binarization preprocessing on the form uploaded after manual inspection, the structure of the form is extracted and stored after character recognition processing, which can effectively improve work efficiency and reduce the error rate. The experimental results show that this experiment has a good result in the realization of electronic operation of the raw material form.