Proceedings ArticleDOI
Degraded document image binarization based on combination of two complementary algorithms
Morteza Valizadeh,Majid Komeili,Narges Armanfard,Ehsanollah Kabir +3 more
- pp 595-599
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TLDR
A new binarization algorithm is proposed that effectively eliminates background and reliably extracts some parts of each character and according to the distance of each pixel form the text, the appropriate algorithm is selected to binarize that pixel.Abstract:
In this paper we combine two binarization algorithms that are complementary to each other. The main idea is to select the better algorithm in each part of document image. There are algorithms that properly distinguish the text from the background in the regions close to the text, but get wrong in the regions far from the text and introduce some part of background as text. We propose a new binarization algorithm that effectively eliminates background and reliably extracts some parts of each character. Then according to the distance of each pixel form the text, the appropriate algorithm is selected to binarize that pixel. Proposed method is applicable for various types of degraded document images. After extensive experiment, the proposed binarization algorithm demonstrate superior performance against four well-know binarization algorithms on a set of degraded document images captured with camera.read more
Citations
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Journal ArticleDOI
Binarization of degraded document image based on feature space partitioning and classification
TL;DR: A new algorithm for the binarization of degraded document images that splits the feature space into text and background regions without using any training dataset and demonstrated superior performance against six well-known algorithms on three datasets.
Journal ArticleDOI
Adaptive binarization of severely degraded and non-uniformly illuminated documents
TL;DR: The proposed method has four steps: contrast analysis, which calculates the local contrast threshold; contrast stretching, thresholding by computing global threshold; and noise removal to improve the quality of binarized image.
Journal ArticleDOI
An adaptive water flow model for binarization of degraded document images
TL;DR: An adaptive water flow model for the binarization of degraded document images that controls the rainfall process in such a way that the water fills up to half of the valley’s depth and classifies the blobs instead of pixels, it preserves stroke connectivity.
Journal ArticleDOI
Binarization of degraded document images based on contrast enhancement
Di Lu,Xin Huang,LiXue Sui +2 more
TL;DR: Compared with five other classical algorithms, the images binarized using the proposed algorithm achieved the highest F-measure and peak signal-to-noise ratio and obtained the highest correct rate of recognition.
Histogram modification for threshold selection
Joan S. Weszka,Azriel Rosenfeld +1 more
TL;DR: In this article, a unified approach for image segmentation is presented, which makes it easier to understand how the methods work and to predict when a particular method is likely to be effective.
References
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A new method for gray-level picture thresholding using the entropy of the histogram
TL;DR: Two methods of entropic thresholding proposed by Pun (Signal Process.,2, 1980, 223–237;Comput.16, 1981, 210–239) have been carefully and critically examined and a new method with a sound theoretical foundation is proposed.
Journal ArticleDOI
Adaptive document image binarization
Jaakko Sauvola,Matti Pietikäinen +1 more
TL;DR: A new method is presented for adaptive document image binarization, where the page is considered as a collection of subcomponents such as text, background and picture, which adapts and performs well in each case qualitatively and quantitatively.
Journal ArticleDOI
Adaptive degraded document image binarization
TL;DR: 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.