Abstract
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.
Highlights
In recent years, Optical Character Recognition (OCR) has been widely applied in the information input of data records on the printed paper
Text images generated many years ago may be limited by sampling devices and encoding algorithms, resulting in low-resolution, text in photos and videos may result in low-resolution after clipping and enlargement, which make the traditional OCR recognition technology unable to fulfil the corresponding requirements
An emerging machine learning technique: generative adversarial network (GAN) is adopted to build a super-resolution processing system to improve the performance of OCR recognition
Summary
OCR has been widely applied in the information input of data records on the printed paper. OCR is the process of converting text image, such as the text on the handwriting document, printed document, scanned document, etc., to the machine-encoded text [1]. Some OCR recognition systems may produce errors in recognizing low-resolution text images This is because low-resolution text images lack highfrequency image details, which makes it difficult for OCR systems to retrieve text information correctly. This problem exists widely in practical applications. A solution for this problem is to perform superresolution processing on low-resolution text images, so as to achieve accurate recognition for the OCR [2]. An emerging machine learning technique: generative adversarial network (GAN) is adopted to build a super-resolution processing system to improve the performance of OCR recognition. The performance of proposed system is evaluated by test datasets
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
