An Efficient Method for Automatic Recognizing Text Fields on Identification Card

Abstract

The problem of optical character and handwriting recognition has been interested by researchers in long time ago. It has obtained great results in theory as well as practical applications. However, the accuracy of identification is still limited, especially in the case of low-quality input images. In this article, we propose an efficient method to recognize information fields for identification in ID card using Convolutional Neural Network (CNN) and Long Short-Term Memory networks (LSTM). The proposed method was trained in a large, various quality dataset including over three thousands ID card image samples. The implementation achieved better results compare to previous studies with the precision, recall and f-measure from over 95 up to over 99% out of all information fields to be recognized.