{"title":"Research of Natural Scene Text Recognition Algorithm Based on OCR","authors":"Yingchun Zhang","doi":"10.36347/sjet.2021.v09i10.002","DOIUrl":null,"url":null,"abstract":"RNN and strengthen the semantic information of the context, BLSTM is used to replace the RNN model for label prediction, and then the CTC algorithm is used to complete the transcription and output the final recognition result. Experimental results show that the improved CRNN text recognition algorithm has an accuracy rate of 96.6%, which is 1% higher than the basic CRNN text recognition algorithm, and this end-to-end network structure design also greatly shortens the text recognition time.","PeriodicalId":379926,"journal":{"name":"Scholars Journal of Engineering and Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scholars Journal of Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36347/sjet.2021.v09i10.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
RNN and strengthen the semantic information of the context, BLSTM is used to replace the RNN model for label prediction, and then the CTC algorithm is used to complete the transcription and output the final recognition result. Experimental results show that the improved CRNN text recognition algorithm has an accuracy rate of 96.6%, which is 1% higher than the basic CRNN text recognition algorithm, and this end-to-end network structure design also greatly shortens the text recognition time.
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