Abstract：Many types and styles of screen printing samples are used in screen printing plate and there are also many targets to be tested on each sample plate, which make the gradient threshold parameter to locate the edge to perform measurement unsuitable. In addition, the method of using the positioning rectangular frame to establish the measurement coordinate system in the traditional visual inspection can cause measurement error. A method for measuring the size of a screen printing template based on machine vision was proposed. A coarse-to-fine measurement strategy was adopted to analyze the information of each type of target to be measured, and the threshold parameters were set in a targeted manner to improve the measurement accuracy. During the measurement process, a hierarchical matching algorithm based on image pyramid and normalized cross-correlation function was used to achieve rough positioning of multiple targets to be measured, and then the threshold parameters obtained by template information statistics were used to perform fine edge positioning to establish local coordinates to complete the measurement. The experimental results showed that the proposed method can effectively improve the measurement accuracy under the same experimental conditions. The average relative error of the improved algorithm is reduced from 4.02% to 1.47%, and the measurement parameters need not be adjusted by users. It is suitable for flexible measurement of different types of screen printing templates.
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2021, Vol. 42 
