Journal ArticleDOI
Adaptive degraded document image binarization
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TLDR
The proposed method does not require any parameter tuning by the user and can deal with degradations which occur due to shadows, non-uniform illumination, low contrast, large signal-dependent noise, smear and strain.About:
This article is published in Pattern Recognition.The article was published on 2006-03-01. It has received 585 citations till now. The article focuses on the topics: Thresholding & Wiener filter.read more
Citations
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Skip Trie Matching for Real-Time OCR Output Error Corrrection on Smartphones
TL;DR: Skip Trie Matching for Real-Time OCR Output Error Correction on Smartphones helps improve the quality of real-time OCR output error correction on smartphones.
Book ChapterDOI
Preprocessing of Document Images Based on the GGD and GMM for Binarization of Degraded Ancient Papyri Images
TL;DR: In this paper, the applicability analysis of the previously proposed preprocessing methods based on the use of the GGD and GMM in combination with various image binarization algorithms for this purpose is presented.
Journal ArticleDOI
Degraded Document Image Enhancing in Spatial Domain using Adaptive Thresholding and Contrasting
Proceedings ArticleDOI
Region-based document image denoising
TL;DR: Test result on UNLV with 11176 samples shows that the average recognition rate rises from 94.44% to 94.85% by using region based image de-noising, which proves that the deficiency of traditional method can be overcome.
References
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Journal Article
Binary codes capable of correcting deletions, insertions, and reversals
Book
Fundamentals of digital image processing
TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.
Journal ArticleDOI
Survey over image thresholding techniques and quantitative performance evaluation
Mehmet Sezgin,Bulent Sankur +1 more
TL;DR: 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images, and the thresholding algorithms that perform uniformly better over nonde- structive testing and document image applications are identified.