Distortion Correction Algorithm for Complex Document Image Based on Multi-level TextDetection

Jisuanji kexue

KOU Xi-chao, ZHANG Hong-rui, FENG Jie, ZHENG Ya-yu¹ 

[1] 1 College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China<

关键词: convolutional neural network|text detection|three-dimensional modeling of documents|document image correction|optical character recognition;   

DOI  :  10.11896/jsjkx.200700072

来源: DOAJ

【 摘 要 】

Document distortion correction is the basic step of document OCR(optical character recognition),which plays an important role in improving the accuracy of OCR.Document image distortion correction often depends on text extraction.However,most of the current document image correction algorithms cannot accurately locate and analyze the text in complex documents,resulting in unsatisfactory correction effects.To address this problem,a text detection framework based on a fully convolutional network is proposed,and the synthetic document is used to train the network to achieve accurate acquisition of three-level text information of characters,words,and text lines.A self-adaptive sampling of text and three-dimensional modeling of the page using a cubic function will transform the correction problem into a model parameter optimization problem to achieve the purpose of correcting complex document images.Correction experiments using synthetic distortion documents and real test data show that the proposed correction method can accurately extract text from complex documents,significantly improve the visual effect of complex document image correction.Compared with other algorithms,the accuracy rate of OCR after correction significantly increa-ses.

【 授权许可】

Unknown