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Improvement Research and Application of Text Recognition Algorithm Based on CRNN

Authors:

Lei Chen,

Shaobin LiAuthors Info & Claims

SPML '18: Proceedings of the 2018 International Conference on Signal Processing and Machine Learning

Pages 166 - 170

https://doi.org/10.1145/3297067.3297073

Published: 28 November 2018 Publication History

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Abstract

This paper is based on CRNN model to recognize the text in the images of football matches scene, and two improvements are proposed. Considering the edge feature of text is strong, this paper adds MFM layers into CRNN model aiming to enhance the contrast. In order to solve the problem of losing details of image static features in the process of getting contextual features, this paper fuses up these two kinds of features. The training and testing experiments carried out on public dataset and manual dataset respectively verify the validity of the improvements, and the recognition accurate rate is higher than original model.

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Cited By

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Henry ASujee R(2023)Medical Prescription Label Reading Using Computer Vision and Deep LearningSoft Computing for Problem Solving10.1007/978-981-19-6525-8_9(97-108)Online publication date: 2-Mar-2023
https://doi.org/10.1007/978-981-19-6525-8_9
Pei BPeng YLuo Y(2021)A method of detecting defects of smart meter LCD screen based on LSD and deep learningMultimedia Tools and Applications10.1007/s11042-020-10481-9Online publication date: 13-Feb-2021
https://doi.org/10.1007/s11042-020-10481-9
Zhang ZDong YYuan Y(2020)Temperature Forecasting via Convolutional Recurrent Neural Networks Based on Time-Series DataComplexity10.1155/2020/35365722020Online publication date: 20-Mar-2020
https://dl.acm.org/doi/10.1155/2020/3536572
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Index Terms

Improvement Research and Application of Text Recognition Algorithm Based on CRNN
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition

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SPML '18: Proceedings of the 2018 International Conference on Signal Processing and Machine Learning

November 2018

177 pages

ISBN:9781450366052

DOI:10.1145/3297067

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 28 November 2018

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SPML '18: 2018 International Conference on Signal Processing and Machine Learning

November 28 - 30, 2018

Shanghai, China

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Henry ASujee R(2023)Medical Prescription Label Reading Using Computer Vision and Deep LearningSoft Computing for Problem Solving10.1007/978-981-19-6525-8_9(97-108)Online publication date: 2-Mar-2023
https://doi.org/10.1007/978-981-19-6525-8_9
Pei BPeng YLuo Y(2021)A method of detecting defects of smart meter LCD screen based on LSD and deep learningMultimedia Tools and Applications10.1007/s11042-020-10481-9Online publication date: 13-Feb-2021
https://doi.org/10.1007/s11042-020-10481-9
Zhang ZDong YYuan Y(2020)Temperature Forecasting via Convolutional Recurrent Neural Networks Based on Time-Series DataComplexity10.1155/2020/35365722020Online publication date: 20-Mar-2020
https://dl.acm.org/doi/10.1155/2020/3536572
Zhang ZLi X(2020)Prediction of Future Appearances via Convolutional Recurrent Neural Networks Based on Image Time Series in Cloud ComputingCloud Computing, Smart Grid and Innovative Frontiers in Telecommunications10.1007/978-3-030-48513-9_27(328-340)Online publication date: 23-May-2020
https://doi.org/10.1007/978-3-030-48513-9_27

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Improving CRNN with EfficientNet-like feature extractor and multi-head attention for text recognition

Feature fusion with covariance matrix regularization in face recognition

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