Document binarisation using Kohonen SOM

Badekas, E.; Papamarkos, Nikos

doi:10.1049/iet-ipr:20050311

Cited by 12 publications

(6 citation statements)

References 31 publications

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“…Although many binarization techniques have been successfully applied to the MediaTeam Oulu Document Database [15], such techniques have difficulty in eliminating background noise on palm leaf manuscripts. Most of the reported work has been carried out on standard images that are not as complex and in poor quality as the ancient palm leaf manuscripts.…”

Section: Discussionmentioning

confidence: 99%

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Comparing Binarisation Techniques for the Processing of Ancient Manuscripts

Chamchong

Fung

Wong

2010

IFIP Advances in Information and Communication Technology

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International audienceAncient manuscripts have been preserved by many organizations so as to protect these documents and retrieve traditional knowledge. With the advanced computer technology, digitized media is now commonly used to record these documents. One objective of such work is to develop an efficient image processing system that could be used to retrieve knowledge and information automatically from these ancient manuscripts. Binarization is a preprocessing technique used to extract text and characters from the manuscripts. The output is then used for further processes such as character recognition and knowledge extraction. This paper compares different binarization techniques that could be used for processing of ancient manuscripts. The aim is to improve the binarization techniques with the main objective of developing an automated preprocessing technique for ancient manuscript recognition and knowledge extraction

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Section: Discussionmentioning

confidence: 99%

“…The criteria may be computed by machine or may be decided by visual human. Within this domain, Badekas and Papamarkos [15], applied some binarization techniques with a standard database (Mediateam Oulu Document) [16]. However, these documents are not as complex as palm leaf manuscripts.…”

Section: Introductionmentioning

confidence: 99%

Comparing Binarisation Techniques for the Processing of Ancient Manuscripts

Chamchong

Fung

Wong

2010

IFIP Advances in Information and Communication Technology

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“…The self-organizing map (SOM) [5,9] is widely applied approach for clustering and pattern recognition that can be used in many stages of the image processing, e. g. in color image segmentation [18], generation of a global ordering of spectral vectors [26], image compression [25], binarisation document [4] etc.…”

Section: Self-organizing Map In Edge Detection Performancementioning

confidence: 99%

Edge Detection in Biomedical Images Using Self-Organizing Maps

Gráfová¹,

Mareš²,

Procházka³

et al. 2013

Artificial Neural Networks - Architectures and Applications

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“…Burgoyne et al (2007) studied binarisation algorithms of greyscale images in optical music recognition by pre-processing that differ significantly from non-music documents; their images are a special sub-case not included in our work. Badekas et al (2007) suggested a system for the binarization of normal and degraded documents for visualisation and recognition of text characters by a Kohonen adaptive neural network (Badekas and Papamarkos, 2007b); this is a realistic advance in real time character recognition. Badekas et al (2007) presented a technique for the binarization of text blocks in colour document images that contain text and graphics highly mixed with the background, based on a colour reduction; this is a common case in Byzantine text images and in our work.…”

Section: Binarization and Thresholdingmentioning

confidence: 99%

Binarization of pre‐filtered historical manuscripts images

Ntogas

Dimitrios

2009

Int Jnl of Intel Comp & Cyber

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to introduce an innovative procedure for digital historical documents image binarization based on image pre-processing and image condition classification. The estimated results for each class of images and each method have shown improved image quality for the six categories of document images described by their separate characteristics. Design/methodology/approach -The applied technique consists of five stages, i.e. text image acquisition, image preparation, denoising, image type classification in six categories according to image condition, image thresholding and final refinement, a very effective approach to binarize document images. The results achieved by the authors' method require minimal pre-processing steps for best quality of the image and increased text readability. This methodology performs better compared to current state-of-the-art adaptive thresholding techniques. Findings -An innovative procedure for digital historical documents image binarization based on image pre-processing, image type classification in categories according to image condition and further enhancement. This methodology is robust and simple, with minimal pre-processing steps for best quality of the image, increased text readability and it performs better compared to available thresholding techniques.Research limitations/implications -The technique consists of limited but optimized pre-processing sequential steps, and attention should be given in document image preparation and denoising, and on image condition classification for thresholding and refinement, since bad results in a single stage corrupt the final document image quality and text readability. Originality/value -The paper contributes in digital image binarization of text images suggesting a procedure based on image preparation, image type classification and thresholding and image refinement with applicability on Byzantine historical documents.

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Document binarisation using Kohonen SOM

Cited by 12 publications

References 31 publications

Comparing Binarisation Techniques for the Processing of Ancient Manuscripts

Comparing Binarisation Techniques for the Processing of Ancient Manuscripts

Edge Detection in Biomedical Images Using Self-Organizing Maps

Binarization of pre‐filtered historical manuscripts images

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