DPM 2D Bar Code Locating based on Corner Detection and Clustering Analysis

Lingling Li, Tao Gao and Yaoquan Yang
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Lingling Li: Department of Automation, North China Electric Power University, Baoding, China
Tao Gao: Department of Automation, North China Electric Power University, Baoding, China & Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand
Yaoquan Yang: Department of Automation, North China Electric Power University, Baoding, China

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), 2015, vol. 7, issue 3, 1-12

Abstract: Industrial DPM bar code is achieved by means of laser etching on metal surface; it uses Data Matrix bar code image as the main carrier, which can ensure the full life cycle tracking ability. But due to the ambient light and metal materials, collected industrial DPM images may exist uneven illumination, low contrast and other issues. How to identify this code type quickly and accurately is a problem, and how to locate the bar code area accurately is even more critical and difficult. In this paper, according to the characteristics of frequently appeared cartesian points in DPM bar code area, an adaptive corner detection method based on curvature scale space is used to detect the corners effectively. Then for the corners gathered by clusters, an improved density-based clustering method is proposed to achieve precise positioning results. Experimental results show that the proposed algorithm has certain suppression ability for low contrast, illumination and blur deformation images and is superior to the traditional algorithms on positioning precision and accuracy.

Date: 2015
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