Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211100038-6.doi: 10.11896/jsjkx.211100038

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Multi-font Printed Uyghur-Kazakh-Kirghiz Keyword Image Recognition

SARDAR Parhat, ABDURAHMAN Kadir, ALIMJAN Yasin   

  1. School of Information Management,Xinjiang University of Finance and Economics,Urumqi 830012,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:SARDAR Parhat,born in 1984,Ph.D.His main research interest includes text and image information retrieval.
    ALIMJAN Yasin,born in 1985,Ph.D.His main research interests include programming language and formal system.
  • Supported by:
    National Natural Science Foundation of China(61662073),2020 Xinjiang Uyghur Autonomeus Ragion Tianchi Doctor Plan Project and Xinjiang University of Finance and Economics School Level Scientific Research Foundation Project(2022XGC022,2022XGC049).

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Abstract: Aiming at the problems of single font type,small size of recognition data,indistinguishable recognition fields and lack of research on Kazakh and Kirghiz printed character recognition,a multi-font printed Uyghur-Kazakh-Kirghiz keyword recognition method based on convolutional neural network(CNN) is proposed.Firstly,aiming at the problem of lack of Uyghur-Kazakh-Kirghiz printed image corpus,based on image synthesis technique,a Uyghur-Kazakh-Kirghiz keyword image data set including 32 font type is constructed.Secondly,using data augmentation technology to add different level of noise,rotation and distortion effects on these images to further reflect the natural scene features of the data set.Thirdly,using a multi-layer CNN network to train the image recognition model on this data set,and obtaining the recognition accuracy over 96.5%,and the accuracy of about 96% is obtained in the actual print image recognition task including 3 commonly used fonts.This method has fewer pre-proces-sing steps and it outperforms previous recognition approaches within the classical machine learning framework.Experimental results show that the recognition method based on synthetic image data can better realize the task of multi-font printed Uyghur-Kazakh-Kirghiz image recognition.

Key words: Uyghur-Kazakh-Kirghiz, OCR, Image synthesis, Convolutional neural network, Keyword image recognition

CLC Number: 

  • TP391
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