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). | VNU Journal of Science Mathematics Physics Vol. 36 No. 1 2020 64-70 Original Article An Efficient Method for Automatic Recognizing Text Fields on Identification Card Nguyen Thi Thanh Tan1 Le Hong Lam2 Nguyen Ha Nam3 1 Faculty of Information Technology Electric Power University Hanoi Vietnam 2 VNU Institute of Information Technology 144 Xuan Thuy Cau Giay Hanoi Vietnam Received 15 January 2020 Revised 21 February 2020 Accepted 26 February 2020 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. Keywords HPC academic industrial applications calculations. 1. Introduction Identification ID Card is a personal card providing basic information of citizen such as full name date of birth place of origin place of permanent residence nationality religion date and place of issue. In almost daily business those information are required and usually extracted manually. It is not efficient process because we need a lot of time to input data one by one. Therefore we need a method that processes automatically known as Optical Character Recognition OCR 1 2 . ____ Corresponding author. Email address https 2588-1124 64 . Tan et al. VNU Journal of Science Mathematics Physics Vol. 36 No. 1 .
