Affiliations: [a] Department of Automation, North China Electric Power University, Baoding, Hebei, China | [b] Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand
Correspondence:
[*]
Corresponding author: Tao Gao, Department of Automation, North China Electric Power University, Baoding 071003, Hebei, China. E-mail:gaotao863@163.com
Abstract:
With the development of two-dimension
code in industrial manufacture, the use of Dotted Data Matrix code is
becoming increasingly wider and deeper due to that it is easy to be marked
on metal or glass surface. A method about processing the complexity and
diversity of Dotted Data Matrix code is presented in this paper. First, the
spot detection is used to get the size of data dot, then a self-adapt hazy
smooth and standardization process is performed for the original image.
Then, a redesigned and optimized Binarization technology is built up to
improve the recognition rate of Binarization Dot-Data Matrix image by a
series of self-adapt smooth changing algorithms. Finally, the recognition of
Dot-Data Matrix code can be achieved by the morphological transform process.
According to the experiment and simulation analysis, the method is fast and
robust, and it is also fit for the requirement of mobile intelligent
terminals.
Keywords: DPM, Dotted Data Matrix, dot detection, binarization, morphological transformation
