Open AccessA Deep Learning Technology based OCR Framework for Recognition Handwritten Expression and Text
Author(s) -
Xuanxia Yao Tuanji Gong
Publication year - 2021
Publication title -
converter
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.104
H-Index - 1
ISSN - 0010-8189
DOI - 10.17762/converter.259
Subject(s) - computer science , artificial intelligence , optical character recognition , component (thermodynamics) , text recognition , intelligent character recognition , intelligent word recognition , character recognition , deep learning , expression (computer science) , pattern recognition (psychology) , speech recognition , natural language processing , character (mathematics) , image (mathematics) , mathematics , thermodynamics , programming language , physics , geometry
Recently Optical character recognition (OCR) based on deep learning technology has achieved great advance and broadly applied in various industries. However it still faces many challenging problems in handwritten text recognition and mathematical expression recognition, such as handwritten Chinese recognition, mixture of printed and handwritten Chinese characters, mathematical expression (ME), chemical equations. In traditional OCR, features selection played a vital role for recognition accuracy, while hand-crafted features are costly and time-consuming. In this paper, we introduce a deep learning based framework to detect and recognize handwritten and printed text or math expression. The framework consists of three components. The first component is DCN (Detection & Classification Network), which based on SSD model to detects and classify mathematical expression and text. The second component consists of text recognition and ME recognition models. The final component merges multiple outputs of the second stage into a whole text. Experiment results show that our framework achieves a relative 10% improvement in mixture of texts and MEs which are printed or handwritten in images. The framework has been deployed for recognition paper or homework at one online education platform.