Paper Info
Title
Automated Image Quality Assessment for Certificates and Bills
Abstract
Auditing of certificates and bills images is pervasive in ERP systems. However, the scanned or camera-captured images sending to an ERP system are not always of good quality. In order to automate the auditing of certificates and bills, and to alleviate the low recognition rate caused by the low quality image in all kinds of certificates and bills automatic analysis and processing system, this paper proposes a method for detecting and filtering out images with low quality, leaving only high quality images, to improve the recognition rate of the auditing of certificates and bills. Unlike other image quality assessment algorithms, which only deal with the blur or noise, the proposed method comprehensively and practically considers a variety of key factors (clarity, color-bias, noise, abnormal brightness areas etc.) which affect the image quality in the process of certificates and bills assessment. The method is applied to detect image quality in certificates and bills automatic verification system, and has achieved good unbiasedness and high sensitivity in real-world ERP applications.
Year
DOI
Venue
2017
10.1109/IEEE.ICCC.2017.8
2017 IEEE International Conference on Cognitive Computing (ICCC)
Keywords
Field
DocType
image quality,certificates and bills,quality assessment,visual system
Data mining,Audit,Automatic image annotation,CLARITY,Computer science,Image processing,Filter (signal processing),Image quality,Digital image processing,Verification system
Conference
ISBN
Citations 
PageRank 
978-1-5386-2009-0
2
0.35
References 
Authors
8
3
Name
Order
Citations
PageRank
Fei Jiang13717.89
Liang-Jie Zhang2982138.17
Huan Chen3208.37