Resolution Enhancement for Low-resolution Text Images Using Generative Adversarial Network

摘要：

　　In recent years,although Optical Character Recognition(OCR)has made considerable progress,low-resolution text images commonly appearing in many scenarios may still cause errors in recognition.For this problem,the technique of Generative Adversarial Network in super-resolution processing is applied to enhance the resolution of low-quality text images in this study.The principle and the implementation in TensorFlow of this technique are introduced.On this basis,a system is proposed to perform the resolution enhancement and OCR for low-resolution text images.The experimental results indicate that this technique could significantly improve the accuracy,reduce the error rate and false rejection rate of low-resolution text images identification.

作者: Jie Kong Congying Wang

作者单位: Xian Shiyou University,School of Computer Science,No.18 2nd Dianzi Road,Xian,China

会议类型: 国际会议

会议名称: 2018 International Symposium on Water System Operations(ISWRSO 2018)(2018年水资源系统及调度国际研讨会)

会议地点: 北京

会议语种:英文

页码: 1-6

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）