Paper Info
Title
Automatic Selection of Parameters for Document Image Enhancement Using Image Quality Assessment
Abstract
Performance of most of the recognition engines for document images is effected by quality of the image being processed and the selection of parameter values for the pre-processing algorithm. Usually the choice of such parameters is done empirically. In this paper, we propose a novel framework for automatic selection of optimal parameters for pre-processing algorithm by estimating the quality of the document image. Recognition accuracy can be used as a metric for document quality assessment. We learn filters that capture the script properties and degradation to predict recognition accuracy. An EM based framework has been formulated to iteratively learn optimal parameters for document image pre-processing. In the E-step, we estimate the expected accuracy using the current set of parameters and filters. In the M-step we compute parameters to maximize the expected recognition accuracy found in E-step. The experiments validate the efficacy of the proposed methodology for document image pre-processing applications.
Year
DOI
Venue
2016
10.1109/DAS.2016.53
2016 12th IAPR Workshop on Document Analysis Systems (DAS)
Keywords
Field
DocType
Document Image Enhancement,Document Image Quality Assessment,Parameter Estimation
Automatic image annotation,Feature detection (computer vision),Pattern recognition,Computer science,Image texture,Image quality,Image processing,Artificial intelligence,Document quality,Estimation theory,Digital image processing
Conference
Citations 
PageRank 
References 
0
0.34
14
Authors
2
Name
Order
Citations
PageRank
ritu garg164.50
Santanu Chaudhury2897127.92