TY - JOUR
T1 - Fast identification method for express end sorting label code based on convolutional recurrent neural network
AU - Du, Haiyan
AU - Wu, Chunxue
AU - Wu, Yan
AU - Han, Ren
AU - Lin, Xiao
AU - Zhang, Sheng
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/11/1
Y1 - 2020/11/1
N2 - In the automatic sorting process of express, the express end sorting label code is used to indicate that the express is dispatched to a specific address by a specific courier. Since there are many areas on the express bill containing digital information, some areas may be improperly photographed, etc. The difficulty in positioning and recognizing the express end sorting label code region is increased. To solve this problem, this paper proposes an express end sorting label code recognition method with convolutional recurrent neural network for the code specification, which has certain versatility. In order to improve the overall code recognition speed, this paper optimizes the traditional digital recognition method, removes the original segmentation operation of the character and recognizes the code as sequence recognition. Firstly, the coding region is located, and then, the express end sorting label code is recognized by the convolutional recurrent neural network. In order to test the experimental performance, this paper tests on Free-Type dataset and SUN-synthesized dataset. The experimental results show that the proposed method improves the recognition accuracy and processing speed of the express end sorting label code.
AB - In the automatic sorting process of express, the express end sorting label code is used to indicate that the express is dispatched to a specific address by a specific courier. Since there are many areas on the express bill containing digital information, some areas may be improperly photographed, etc. The difficulty in positioning and recognizing the express end sorting label code region is increased. To solve this problem, this paper proposes an express end sorting label code recognition method with convolutional recurrent neural network for the code specification, which has certain versatility. In order to improve the overall code recognition speed, this paper optimizes the traditional digital recognition method, removes the original segmentation operation of the character and recognizes the code as sequence recognition. Firstly, the coding region is located, and then, the express end sorting label code is recognized by the convolutional recurrent neural network. In order to test the experimental performance, this paper tests on Free-Type dataset and SUN-synthesized dataset. The experimental results show that the proposed method improves the recognition accuracy and processing speed of the express end sorting label code.
KW - Code positioning
KW - Convolutional recurrent neural network
KW - Express end
KW - Label code recognition
KW - Sequence recognition
UR - https://www.scopus.com/pages/publications/85086864370
U2 - 10.1007/s11760-020-01703-6
DO - 10.1007/s11760-020-01703-6
M3 - 文章
AN - SCOPUS:85086864370
SN - 1863-1703
VL - 14
SP - 1689
EP - 1697
JO - Signal, Image and Video Processing
JF - Signal, Image and Video Processing
IS - 8
ER -