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     Research Journal of Applied Sciences, Engineering and Technology


Adaptive Segmentation Method for 2-D Barcode Image Base on Mathematic Morphological

1, 2Jianhua Li, 1Yi-Wen Wang, 1Yi Chen and 1Guocheng Wang
1Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China, Chengdu 610054, China
2Information Engineer School of Nanchang University, Nanchang 330031, China
Research Journal of Applied Sciences, Engineering and Technology  2013  18:3335-3342
http://dx.doi.org/10.19026/rjaset.6.3644  |  © The Author(s) 2013
Received: August 03, 2012  |  Accepted: September 03, 2012  |  Published: October 10, 2013

Abstract

Segmentation is a key process of 2-D barcode identification. In this study we propose a fast adaptive segmentation method that is based on morphological method which is suitable for kinds of 2-D barcode images with different scale, angle and sort. The algorithm is based on mathematical morphology, the basic idea of the algorithm is to use Multi-scale open reconstruction of mathematical morphology to transform the image continuously, then choose whether to terminate by the results of the adjacent image transformation and finally get the final segmentation results by further processing of the images obtain from termination.The proposed approach is applied in experiments on 2-D barcodes with complicated background. The results indicated that the proposed method is very effective in adaptively 2-D barcode image segmentation.

Keywords:

2-D barcode, mathematical morphology, morphological segmentation, reconstruction, structure element,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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