TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text

Medhat, Fady1; Mohammadi, Mahnaz1; Jaf, Sardar1; Willcocks, Chris G.1; Breckon, Toby P.1; Matthews, Peter1; McGough, Andrew Stephen2; Theodoropoulos, Georgios3; Obara, Boguslaw1

10.1109/BigData.2018.8622136

2018

2639-1589

978-1-5386-5036-3

2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)

2986-2994

10-13 Dec. 2018

Seattle, WA, United states

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Handling large corpuses of documents is of significant importance in many fields, no more so than in the areas of crime investigation and defence, where an organisation may be presented with a large volume of scanned documents which need to be processed in a finite time. However, this problem is exacerbated both by the volume, in terms of scanned documents and the complexity of the pages, which need to be processed. Often containing many different elements, which each need to be processed and understood. Text recognition, which is a primary task of this process, is usually dependent upon the type of text, being either handwritten or machine-printed. Accordingly, the recognition involves prior classification of the text category, before deciding on the recognition method to be applied. This poses a more challenging task if a document contains both handwritten and machine-printed text. In this work, we present a generic process flow for text recognition in scanned documents containing mixed handwritten and machine-printed text without the need to classify text in advance. We realize the proposed process flow using several open-source image processing and text recognition packages. The evaluation is performed using a specially developed variant, presented in this work, of the IAM handwriting database, where we achieve an average transcription accuracy of nearly 80% for pages containing both printed and handwritten text.

big data unstructured data Optical Character Recognition (OCR) Handwritten Text Recognition (HTR) machine-printed text recognition IAM handwriting database TMIXT

其他

英语

CPCI-S ; EI

Istituto Superiore di Sanità[]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods

WOS:000468499303009

20191106615762

Big data ; Copying ; Image processing ; Optical character recognition ; Optical data processing ; Transcription

Biology:461.9 ; Data Processing and Image Processing:723.2 ; Light/Optics:741.1 ; Reproduction, Copying:745.2 ; Information Sources and Analysis:903.1

Web of Science

1.Univ Durham, Dept Comp Sci, Durham, England
2.Newcastle Univ, Sch Comp, Newcastle Upon Tyne, Tyne & Wear, England
3.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Peoples R China

Medhat, Fady,Mohammadi, Mahnaz,Jaf, Sardar,et al. TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2018:2986-2994.