The text detection algorithm for agricultural materials image based on Ghost module and its application
In response to problems such as slow detection speed of text in agricultural materials image and lack of mobile applications,based on the agricultural materials image dataset,a Ghost module-based text detection algorithm for agricultural materials image was proposed,which improved the DB network,used the MobileNetv2 network to extract the base features,introduced a multi-scale fea-ture fusion module to obtain feature fusion between multiple layers,and used a differentiable binary post-processing algorithm to pre-dict the text,making it possible to quickly detect the text in agricultural materials image.The accuracy of the algorithm on the agricul-tural materials image dataset was basically up to the standard of mainstream algorithms,with a detection speed of 18.6 img/s and a cen-sus count of 2.99 M,with lightweight features,and the algorithm was deployed to mobile devices and ran successfully.
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