A Method for Segmentation of Vietnamese Identification Card Text Fields

Thanh, Tan Nguyen Thi; Nguyen, Kim Phi Phung

doi:10.14569/ijacsa.2019.0101057

Cited by 4 publications

(6 citation statements)

References 17 publications

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“…Works [22] and [23] describe systems for Vietnamese identity documents text fields detection and recognition. The pre-processing steps in [23] include greyscaling, tilt correction, smoothing and binarization, and the text fields are separately detected with ID card number detection on the one side of the document, and table structure analysis for the other side.…”

Section: Related Workmentioning

confidence: 99%

Towards a unified framework for identity documents analysis and recognition

Bulatov¹,

Bezmaternykh²,

Nikolaev

et al. 2022

Computer Optics

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Identity documents recognition is far beyond classical optical character recognition problems. Automated ID document recognition systems are tasked not only with the extraction of editable and transferable data but with performing identity validation and preventing fraud, with an increasingly high cost of error. A significant amount of research is directed to the creation of ID analysis systems with a specific focus for a subset of document types, or a particular mode of image acquisition, however, one of the challenges of the modern world is an increasing demand for identity document recognition from a wide variety of image sources, such as scans, photos, or video frames, as well as in a variety of virtually uncontrolled capturing conditions. In this paper, we describe the scope and context of identity document analysis and recognition problem and its challenges; analyze the existing works on implementing ID document recognition systems; and set a task to construct a unified framework for identity document recognition, which would be applicable for different types of image sources and capturing conditions, as well as scalable enough to support large number of identity document types. The aim of the presented framework is to serve as a basis for developing new methods and algorithms for ID document recognition, as well as for far more heavy challenges of identity document forensics, fully automated personal authentication and fraud prevention.

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Section: Related Workmentioning

confidence: 99%

Towards a unified framework for identity documents analysis and recognition

Bulatov¹,

Bezmaternykh²,

Nikolaev

et al. 2022

Computer Optics

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“…In this study, we consider the input images are front side images of CID cards. Traditional approaches based on image processing techniques were proposed to localize and detect card images from the background [3][4][5]7,30]. Almost these approaches included some main steps as binarization, edge detection, straight line detection, corners detection, and post-processing.…”

Section: Croppermentioning

confidence: 99%

“…Text recognition has been successfully used to extract information from the identity card (ID card) for different languages such as English, Chinese, Vietnamese, Spanish, etc. [3][4][5][6][7]. This study focuses on developing an approach to recognize Vietnamese text and an application to extract information from Vietnamese citizen identity card (CID carda.k.a.…”

Section: Introductionmentioning

confidence: 99%

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An improved CRNN for Vietnamese Identity Card Information Recognition

Dat¹,

Dang²,

Truong³

et al. 2022

Computer Systems Science and Engineering

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This paper proposes an enhancement of an automatic text recognition system for extracting information from the front side of the Vietnamese citizen identity (CID) card. First, we apply Mask-RCNN to segment and align the CID card from the background. Next, we present two approaches to detect the CID card's text lines using traditional image processing techniques compared to the EAST detector. Finally, we introduce a new end-to-end Convolutional Recurrent Neural Network (CRNN) model based on a combination of Connectionist Temporal Classification (CTC) and attention mechanism for Vietnamese text recognition by jointly train the CTC and attention objective functions together. The length of the CTC's output label sequence is applied to the attention-based decoder prediction to make the final label sequence. This process helps to decrease irregular alignments and speed up the label sequence estimation during training and inference, instead of only relying on a data-driven attention-based encoder-decoder to estimate the label sequence in long sentences. We may directly learn the proposed model from a sequence of words without detailed annotations. We evaluate the proposed system using a real collected Vietnamese CID card dataset and find that our method provides a 4.28% in WER and outperforms the common techniques.

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“…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.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Method for Automatic Recognizing Text Fields on Identification Card

Tan¹,

Nam²

2020

MaP

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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.

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A Method for Segmentation of Vietnamese Identification Card Text Fields

Cited by 4 publications

References 17 publications

Towards a unified framework for identity documents analysis and recognition

Towards a unified framework for identity documents analysis and recognition

An improved CRNN for Vietnamese Identity Card Information Recognition

An Efficient Method for Automatic Recognizing Text Fields on Identification Card

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