On‐line print‐defect detecting in an incremental subspace learning framework
Abstract
Purpose
The purpose of this paper is to propose a novel on‐line print‐defect detecting approach.
Design/methodology/approach
The proposed method uses incremental principal component analysis (IPCA) to model a variety pattern with respect to the detected image itself.
Findings
The algorithm is constructed and deployed to a real‐time detecting print‐defect system, and the test results show that the system reduces false alarms dramatically.
Originality/value
The paper describes groundbreaking work which, for the first time in the printing industry, uses IPCA in relation to print‐defect detecting.
Keywords
Citation
Sun, X., Zhang, L. and Chen, B. (2011), "On‐line print‐defect detecting in an incremental subspace learning framework", Sensor Review, Vol. 31 No. 2, pp. 138-143. https://doi.org/10.1108/02602281111109998
Publisher
:Emerald Group Publishing Limited
Copyright © 2011, Emerald Group Publishing Limited