A Background Subtraction Method for Defect Detection of Printed Image

Abstract:

Background subtraction is often used to detect the moving objects from static cameras. The difficult of defect detecting of printing matter is how to detect the unknown flaws in complicate background effectively. Inspired by the background modeling approach for moving objects detection, a background modeling method in defect detection of printed image is suggested in this paper. Those pixels without defects are regarded as background, while the flaw pixels are defined as foreground. Firstly, we select LBP histogram as texture feature and HSV histogram as color feature to model the background respectively. Then, lots of printed images in which there are no defects are used to update these two models. Finally, we utilize the models to detect defects of printing images. Experimental results show that this background model works well in our defect detection.

• Periodical: Applied Mechanics and Materials (Volumes 462-463)
• Pages: 421-427
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.462-463.421
• Online since: November 2013
• Authors: Jian Hua Ding, Yao Lu, Wei Huang, Ming Qin
• Keywords: Background Modeling, Defect Detection, Foreground Detection, Printed Image

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