Barcode detection and decoding method based on deep learning

Traditional Barcode detection methods are susceptible to environment. It is very difficult to implement bar code detection in complex backgrounds and on-site environments. Barcode detection is mainly divided into two processes of positioning and data decoding. In this paper, a bar code detection method based on deep learning is proposed. The method is based on the single-shot mutibox detector (SSD) method, which can meet the requirements of high speed and high precision. In this paper, the SSD method is used to detect the position of the barcode, and then the image processing method is used to segment the barcode. Then the morphological method and the barcode correction method are used to complete the decoding of the barcode data. The test results on the actual data set show that our method can stably and quickly complete the process of positioning and decoding the barcode.