On‐line print‐defect detecting in an incremental subspace learning framework

Abstract

PurposeThe purpose of this paper is to propose a novel on‐line print‐defect detecting approach.Design/methodology/approachThe proposed method uses incremental principal component analysis (IPCA) to model a variety pattern with respect to the detected image itself.FindingsThe 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/valueThe paper describes groundbreaking work which, for the first time in the printing industry, uses IPCA in relation to print‐defect detecting.