Paper Info
Title
Character-Based Automated Human Perception Quality Assessment in Document Images
Abstract
Large degradations in document images impede their readability and deteriorate the performance of automated document processing systems. Document image quality (IQ) metrics have been defined through optical character recognition (OCR) accuracy. Such metrics, however, do not always correlate with human perception of IQ. When enhancing document images with the goal of improving readability, e.g., in historical documents where OCR performance is low and/or where it is necessary to preserve the original context, it is important to understand human perception of quality. The goal of this paper is to design a system that enables the learning and estimation of human perception of document IQ. Such a metric can be used to compare existing document enhancement methods and guide automated document enhancement. Moreover, the proposed methodology is designed as a general framework that can be applied in a wide range of applications.
Year
DOI
Venue
2012
10.1109/TSMCA.2011.2170417
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions
Keywords
Field
DocType
document image processing,image enhancement,optical character recognition,OCR accuracy,automated document enhancement,automated document processing systems,character-based automated human perception quality assessment,document IQ,document image quality metrics,human perception,optical character recognition accuracy,readability,Document imaging,feature extraction,human–machine interactions,image enhancement,learning systems,perception quantification,quality metrics
Document imaging,Information retrieval,Computer science,Document processing,Image quality,Optical character recognition,Feature extraction,Readability,Perception,Optical character recognition software
Journal
Volume
Issue
ISSN
42
3
1083-4427
Citations 
PageRank 
References 
13
0.71
21
Authors
2
Name
Order
Citations
PageRank
Tayo Obafemi-Ajayi1254.83
Gady Agam239143.99