Evaluation Of Human Perception Of Degradation In Document Images

Abstract

Large degradations in document images impede their readability as well as substantially deteriorating the performance of automated document processing systems. Image quality metrics have been defined to correlate with OCR accuracy. However, this does not always correlate with human perception of image quality. When enhancing document images with the goal of improving readability, it is important to understand human perception of quality. The goal of this work is to evaluate human perception of degradation and correlate it to known degradation parameters and existing image quality metrics. The information captured enables the learning and estimation of human perception of document image quality. © 2009 Copyright SPIE - The International Society for Optical Engineering.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Document degradation models; Document image analysis; Image quality; Machine learning

International Standard Book Number (ISBN)

978-081947927-3

International Standard Serial Number (ISSN)

0277-786X

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2023 Society of Photo-optical Instrumentation Engineers, All rights reserved.

Publication Date

29 Mar 2010

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