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A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition [article]

Andre G. Hochuli, Alceu S. Britto Jr, David A. Saji, Jose M. Saavedra, Robert Sabourin, Luiz S. Oliveira
2020 arXiv   pre-print
Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby imposing substantial constraints  ...  It achieved a 97%, 96%, and 84% recognition rate on the NIST-SD19, CAR, and CVL datasets, respectively.  ...  Acknowledgements This research was supported by The National Council for Scientific and Technological Development  ... 
arXiv:2010.15904v1 fatcat:rsf4n4o67vcqrnfemqoqnib6hy

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition [article]

Zhao Zhang, Zemin Tang, Zheng Zhang, Yang Wang, Jie Qin, Meng Wang
2020 arXiv   pre-print
The recognition results on large-scale Chinese string and MNIST datasets show that our IntensiveNet can deliver enhanced recog-nition results, compared with other related deep models.  ...  By adding short connections to different layers, the feature flow and coupling between layers are enhanced.  ...  ACKNOWLEDGEMENTS This paper is partially supported by the National Natural Science Foundation of China (61672365, 61732008, 61725203, 61622305, 61871444 and 61806035), and the Fundamental Research Funds  ... 
arXiv:1912.06446v2 fatcat:4ooeoa7qbrev5lxfw2gftrw74u

HDSR-Flor: A Robust End-to-End System to Solve the Handwritten Digit String Recognition Problem in Real Complex Scenarios

Arthur Flor De Sousa Neto, Byron Leite Dantas Bezerra, Estanislau Baptista Lima, Alejandro Hector Toselli
2020 IEEE Access  
INTRODUCTION H ANDWRITTEN Digit String Recognition (HDSR) has attracted intense attention in recent years as an academic research topic, due to its vast applications in industry [1] .  ...  RELATED WORKS There are several approaches to deal with digit recognition through Handwritten Digit String Recognition (HDSR) systems.  ...  Through fruitful partnerships with companies, Byron has contributed to the design and improvement of document capture and imaging systems, forms processing, handwriting recognition, and signature verification  ... 
doi:10.1109/access.2020.3039003 fatcat:iy3xqnviqjgu7a2jj3llkjj75i

A Sequential Handwriting Recognition Model Based on a Dynamically Configurable CRNN

Ahmed AL-Saffar, Suryanti Awang, Wafaa AL-Saiagh, Ahmed Salih AL-Khaleefa, Saad Adnan Abed
2021 Sensors  
Handwriting recognition refers to recognizing a handwritten input that includes character(s) or digit(s) based on an image.  ...  Because most applications of handwriting recognition in real life contain sequential text in various languages, there is a need to develop a dynamic handwriting recognition system.  ...  [57] proposed a fixed CNN architecture for handwritten digit recognition tasks.  ... 
doi:10.3390/s21217306 pmid:34770612 pmcid:PMC8587523 fatcat:o2umjghgcvccrb7g3tonz4nf34

Compressed DenseNet for Lightweight Character Recognition [article]

Zhao Zhang, Zemin Tang, Yang Wang, Haijun Zhang, Shuicheng Yan, Meng Wang
2020 arXiv   pre-print
LDB is a convolutional block similarly as dense block, but it can reduce the computation cost and weight size to (1/L, 2/L), compared with original ones, where L is the number of layers in blocks.  ...  To reduce the computing cost and weight size, we re-define and re-design the way of combining internal features of the dense blocks.  ...  another convolutional group without 1*1 convolution.  We conduct the character recognition tasks on the Chinese string and handwritten digits, which verifies that our proposed network can effectively  ... 
arXiv:1912.07016v3 fatcat:lpbzmn7wirgxhkf33xl4eedgda

Dense Residual Network: Enhancing Global Dense Feature Flow for Character Recognition [article]

Zhao Zhang, Zemin Tang, Yang Wang, Zheng Zhang, Choujun Zhan, Zhengjun Zha, Meng Wang
2021 arXiv   pre-print
Technically, we propose an efficient and effective CNN framework, i.e., Fast Dense Residual Network (FDRN), for text recognition.  ...  To construct FDRN, we propose a new fast residual dense block (f-RDB) to retain the ability of local feature fusion and local residual learning of original RDB, which can reduce the computing efforts at  ...  It is noteworthy to point out that CTC is required in the first task of character recognition, but is not needed in the second handwritten digits recognition task.  ... 
arXiv:2001.09021v4 fatcat:mnbea2lk5jfjvjak65w3f6r7ua

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition [article]

Zecheng Xie, Zenghui Sun, Lianwen Jin, Hao Ni, Terry Lyons
2017 arXiv   pre-print
Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences.  ...  and prior knowledge about a certain language in the recognition procedure.  ...  ACKNOWLEDGMENT TL and HN are supported by the Alan Turing Institute under the EPSRC grant EP/N510129/1. TL is also supported by ERC advanced grant ESig (agreement no. 291244).  ... 
arXiv:1610.02616v2 fatcat:qbx7rjazhvhezps43qdg3gzoa4

A Pipeline Approach to Context-Aware Handwritten Text Recognition

Yee Fan Tan, Tee Connie, Michael Kah Ong Goh, Andrew Beng Jin Teoh
2022 Applied Sciences  
Despite concerted efforts towards handwritten text recognition, the automatic location and transcription of handwritten text remain a challenging task.  ...  After that, the text sequences are fed to a Residual Network with a Transformer (ResNet-101T) model to perform transcription.  ...  Recognition of handwritten text and text-line CTPN to detect text lines, MLC-CRNN for text recognition 3883 training images and 297 testing images Accuracy of 91.4% Sign and Karayev (2021) [4] Full-page  ... 
doi:10.3390/app12041870 fatcat:fsq3bztcqnaizbpy2obwjeglye

Improving CNN-BGRU Hybrid Network for Arabic Handwritten Text Recognition

Sofiene Haboubi, Tawfik Guesmi, Badr M Alshammari, Khalid Alqunun, Ahmed S Alshammari, Haitham Alsaif, Hamid Amiri
2022 Computers Materials & Continua  
As an exception, handwritten Arabic script has many objectives that remain to be overcome, given its complex form, their number of forms which exceeds 100 and its cursive nature.  ...  To test the recognition capacity of BGRU, the proposed architecture is composed by 6 convolutional neural network (CNN) blocks for feature extraction and 1 BGRU + 2 dense layers for learning and test.  ...  On a database of digits, Suvarnam showed the capacity of its system by a recognition rate of 100%.  ... 
doi:10.32604/cmc.2022.029198 fatcat:obf7csetkfb43mpkkgqva7o2wi

LexiconNet: An End-to-End Handwritten Paragraph Text Recognition System [article]

Lalita Kumari, Sukhdeep Singh, Vaibhav Varish Singh Rathore, Anuj Sharma
2022 arXiv   pre-print
Historical documents present in the form of libraries needs to be digitised. The recognition of these unconstrained cursive handwritten documents is a challenging task.  ...  These processes are prone to errors that create bottleneck in the recognition accuracies.  ...  INTRODUCTION A Handwritten Text Recognition (HTR) system understands handwritten text written on digital surface, on paper or any other media.  ... 
arXiv:2205.11018v1 fatcat:mivtyg6u7vghtp45bycaaoyjhy

A Survey of Historical Document Image Datasets [article]

Konstantina Nikolaidou, Mathias Seuret, Hamam Mokayed, Marcus Liwicki
2022 arXiv   pre-print
We summarize each study by assigning it to one of three pre-defined tasks: document classification, layout structure, or semantic analysis.  ...  This paper presents a systematic literature review of image datasets for document image analysis, focusing on historical documents, such as handwritten manuscripts and early prints.  ...  A digit detection and recognition system named DIGITNET was proposed that initially detects handwritten digits and passes the output to a recognition network to classify them.  ... 
arXiv:2203.08504v2 fatcat:ilgqqgylfzejnpccrsg7vfsncm

Deep Learning for Historical Document Analysis and Recognition—A Survey

Francesco Lombardi, Simone Marinai
2020 Journal of Imaging  
This analysis shows that the latest research is a leap forward since it is not the simple use of recently proposed algorithms to previous problems, but novel tasks and novel applications of state of the  ...  The analysis and recognition of historical documents, as we survey in this work, is not an exception.  ...  [81] implement an end to end model of deep CRNN for handwritten Japanese text lines recognition.  ... 
doi:10.3390/jimaging6100110 pmid:34460551 pmcid:PMC8321201 fatcat:nevh2ctshzfwtey4girgjtaftq

Improving Script Identification by Integrating Text Recognition Information

Yupeng Cao, Jing Li, Qiu-Feng Wang, Kaizhu Huang, Rui Zhang
2019 Australian Journal of Intelligent Information Processing Systems  
In the second stage, we recognize scene text by a multi-lingual recognition system, then we propose a fusion CNN to integrate the recognized text information and classification scores from the first stage  ...  In the first stage, we utilize a Residual Neural Network (ResNet) based method to get a preliminary classification result.  ...  Based on multiple successful application of RNNs [21, 22] , Shi et al. [23] proposed an end-to-end trainable neural network (CRNN) for STR that is a combination of CNN and RNN.  ... 
dblp:journals/ajiips/CaoLWHZ19 fatcat:6jqvd3ifjzbdfpsgef5mzbety4

Cursive Text Recognition in Natural Scene Images using Deep Convolutional Recurrent Neural Network

Asghar Ali Chandio, Md. Asikuzzaman, Mark R. Pickering, Mehwish Leghari
2022 IEEE Access  
To increase the text recognition accuracy further, we explore deeper CNN architectures like VGG-16, VGG-19, ResNet-18 and ResNet-34 to extract more appropriate Urdu text features, and compare the recognition  ...  The experimental results show that the proposed deep CRNN network with shortcut connections outperform than other network architectures.  ...  ACKNOWLEDGMENTS The first author is thankful to the University of New South Wales, Australia, for supporting his Ph.D. candidature with a scholarship.  ... 
doi:10.1109/access.2022.3144844 fatcat:qmyrwvwgercpnbk6zxkmx6yani

Continuous Offline Handwriting Recognition using Deep Learning Models [article]

Jorge Sueiras
2021 arXiv   pre-print
The transcription of handwritten content present in digitized documents is significant in analyzing historical archives or digitizing information from handwritten documents, forms, and communications.  ...  The generalization capacity of the model has also been validated by evaluating it on three handwritten text databases using different languages: IAM in English, RIMES in French, and Osborne in Spanish,  ...  application to the offline handwritten recognition problem.  ... 
arXiv:2112.13328v1 fatcat:xkcdw7c2rngd7jsaixsfosqzc4
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