Handwritten billet number recognition algorithm based on edge extraction  

作　　者：ZONG Dexiang SHI Guifen HE Yonghui 

机构地区：[1]Research Institute,Baoshan Iron&Steel Co.,Ltd.,Shanghai 201999,China

出　　处：《Baosteel Technical Research》2021年第3期22-27,共6页宝钢技术研究（英文版）

摘　　要：Character recognition has always been a hot topic in the field of computer vision.However,it is often difficult to obtain high-precision results in the actual scene owing to factors such as lighting conditions and imaging angle.Aiming at the problem of handwritten billet identification in the steel industry,this paper proposes the use of the canny edge extraction method to enhance the contour characteristics of characters.This technique is combined with the object detection network to achieve the automatic identification of blank square numbers and solve the problem of automatic tracking of billet logistics in the production process.The proposed algorithm is applied to the site with more than 2019 images containing characters in the test set.Results show that the proposed algorithm has good practical application potential.

关 键 词：billet character recognition character rotation mechanism canny operator deep learning network 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]