Fast identification method for express end sorting label code based on convolutional recurrent neural network
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ORIGINAL PAPER
Fast identification method for express end sorting label code based on convolutional recurrent neural network Haiyan Du1 · Chunxue Wu1
· Yan Wu2 · Ren Han1 · Xiao Lin3 · Sheng Zhang1
Received: 15 May 2019 / Revised: 12 October 2019 / Accepted: 27 April 2020 © The Author(s) 2020
Abstract 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. Keywords Express end · Code positioning · Label code recognition · Sequence recognition · Convolutional recurrent neural network
1 Introduction Optical character recognition (OCR) is an important research field in the field of pattern recognition [1, 2]. It combines digital image processing, computer graphics and artificial
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Sheng Zhang [email protected] Haiyan Du [email protected] Chunxue Wu [email protected] Yan Wu [email protected] Ren Han [email protected] Xiao Lin [email protected]
1
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2
The School of Public and Environmental Affairs, Indiana University, Bloomington 47405, USA
3
The Department of Computer Science, Shanghai Normal University, Shanghai 201400, China
intelligence. Digital recognition [3, 4] is also an important research direction and component of OCR. Therefore, it has attracted a large number of scholars to study digital recognition. In the intelligent express sorting system, as long as the express end sorting label code is obtained, the address that the express is sent by the courier can be known. If the process of express sorting can be automatically processed by the computer, and the express end sorting label code is automatically extracted and accurately identified from the express bill, the time and effort for manually processing the data can be saved. Therefore, it is especially important to automatically recognize the express end sorti
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