In the printing industry, defect detection is of crucial importance for ensuring the quality\nof printed matter. However, rarely has research been conducted for web offset printing. In this\npaper, we propose an automatic defect detection method for web offset printing, which consists of\ndetermining first row of captured images, image registration and defect detection. Determining\nthe first row of captured images is a particular problem of web offset printing, which has not been\nstudied before. To solve this problem, a fast computational algorithm based on image projection\nis given, which can convert 2D image searching into 1D feature matching. For image registration,\na shape context descriptor is constructed by considering the shape concave-convex feature, which can\neffectively reduce the dimension of features compared with the traditional image registration method.\nTo tolerate the position difference and brightness deviation between the detected image and the\nreference image, a modified image subtraction is proposed for defect detection. The experimental\nresults demonstrate the effectiveness of the proposed method.
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