An adaptive container code character segmentation algorithm

DOI

10.2991/mmebc-16.2016.157How to use a DOI?

Keywords

adaptive, container code, character segmentation, morphology, projection.

Abstract

Container character segmentation is an important step of the container code intelligent recognition system, which greatly affects the subsequent character recognition work. In order to quickly segment a variety of container characters, an adaptive container character segmentation algorithm was proposed under the complex situation. The filtering operation was implemented on the extracted multiple code area; then it is determined whether that the container code is arranged in a row, a column or multiple rows according to the high-width ratio; finally, the character segmentation is performed on the filtered code images. First, the morphology dilation with the vertical linear structural elements and the left-right bound projection location were used to perform the segmentation task of the characters arranging in a row. Secondly, the morphological dilation with the horizontal structural elements and the upper-low bound projection location were used to perform the segmentation task of the characters arranging in a column. Finally, for the multiply row code characters image, it was divided into multiple character areas where each is in a row or column. Experimental results show that this method can accurately, quickly and adaptive segment the container character images in a row, a column or multiple rows under the complex background.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yajie Zhu
AU  - Chenglong Liang
PY  - 2016/06
DA  - 2016/06
TI  - An adaptive container code character segmentation algorithm
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 739
EP  - 744
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.157
DO  - 10.2991/mmebc-16.2016.157
ID  - Zhu2016/06
ER  -