TY - GEN
T1 - Barcode detection and decoding method based on deep learning
AU - Ren, Yiming
AU - Liu, Zhen
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - 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.
AB - 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.
KW - Affine transformation correction
KW - Barcode detection
KW - Deep learning
KW - Morphological method
UR - https://www.scopus.com/pages/publications/85084932048
U2 - 10.1109/ICISCAE48440.2019.217911
DO - 10.1109/ICISCAE48440.2019.217911
M3 - 会议稿件
AN - SCOPUS:85084932048
T3 - 2019 2nd International Conference on Information Systems and Computer Aided Education, ICISCAE 2019
SP - 393
EP - 396
BT - 2019 2nd International Conference on Information Systems and Computer Aided Education, ICISCAE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Information Systems and Computer Aided Education, ICISCAE 2019
Y2 - 28 September 2019 through 30 September 2019
ER -