Abstract
This paper addresses this challenge by using machine vision to firstly collect cigarette box image data and process the images with grayscale and binarization, and then extract the characters to be trained by extracting the region of interest and doing threshold segmentation in turn. The SVM classifier was used to train the extracted characters, and finally the characters were recognized in turn, and the recognition effects of different classifiers were compared and analyzed, and it was concluded that the SVM classifier has the best effect and is suitable for enterprise production.
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