Improving the quality of degraded document images
It is common for libraries to provide public access to historical and ancient document image collections. It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarization approach for...
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creator | Kavallieratou, E. Stamatatos, E. |
description | It is common for libraries to provide public access to historical and ancient document image collections. It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarization approach for improving the quality of old documents using a combination of global and local thresholding. First, a global thresholding technique specifically designed for old document images is applied to the entire image. Then, the image areas that still contain background noise are detected and the same technique is re-applied to each area separately. Hence, we achieve better adaptability of the algorithm in cases where various kinds of noise coexist in different areas of the same image while avoiding the computational and time cost of applying a local thresholding in the entire image. Evaluation results based on a collection of historical document images indicate that the proposed approach is effective in removing background noise and improving the quality of degraded documents while documents already in good condition are not affected |
doi_str_mv | 10.1109/DIAL.2006.23 |
format | Conference Proceeding |
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It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarization approach for improving the quality of old documents using a combination of global and local thresholding. First, a global thresholding technique specifically designed for old document images is applied to the entire image. Then, the image areas that still contain background noise are detected and the same technique is re-applied to each area separately. Hence, we achieve better adaptability of the algorithm in cases where various kinds of noise coexist in different areas of the same image while avoiding the computational and time cost of applying a local thresholding in the entire image. 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It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarization approach for improving the quality of old documents using a combination of global and local thresholding. First, a global thresholding technique specifically designed for old document images is applied to the entire image. Then, the image areas that still contain background noise are detected and the same technique is re-applied to each area separately. Hence, we achieve better adaptability of the algorithm in cases where various kinds of noise coexist in different areas of the same image while avoiding the computational and time cost of applying a local thresholding in the entire image. Evaluation results based on a collection of historical document images indicate that the proposed approach is effective in removing background noise and improving the quality of degraded documents while documents already in good condition are not affected</description><subject>Background noise</subject><subject>Capacitive sensors</subject><subject>Computational efficiency</subject><subject>Cultural differences</subject><subject>Degradation</subject><subject>Image analysis</subject><subject>Lighting</subject><subject>Pixel</subject><subject>Software libraries</subject><subject>Systems engineering and theory</subject><isbn>0769525318</isbn><isbn>9780769525310</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjUtLw0AURgdEUGt37tzMH0icO7fzyLLUVyDgpl2Xydw7MdI0NUmF_nsD-m0OnMX5hHgAlQOo4um5XFe5VsrmGq_EnXK2MNog-BuxHMcvNQ-LlYXVrYCyOw39T3ts5PTJ8vscDu10kX2SxM0QiElSH88dHyfZdqHh8V5cp3AYefnPhdi9vmw371n18VZu1lUWNfgp0y4GFbSPnjjW0TlgY01wFE20rk6efG3YkEe2hIkVJSI7S_QmRYW4EI9_3ZaZ96dhfh8ue7CgC2fxF3dAQpA</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Kavallieratou, E.</creator><creator>Stamatatos, E.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2006</creationdate><title>Improving the quality of degraded document images</title><author>Kavallieratou, E. ; Stamatatos, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c218t-27ca0a28c8decbc771e565a7dc5c67bf8d8b5e5d83e6d3fe0dfdd6d8b385fc033</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Background noise</topic><topic>Capacitive sensors</topic><topic>Computational efficiency</topic><topic>Cultural differences</topic><topic>Degradation</topic><topic>Image analysis</topic><topic>Lighting</topic><topic>Pixel</topic><topic>Software libraries</topic><topic>Systems engineering and theory</topic><toplevel>online_resources</toplevel><creatorcontrib>Kavallieratou, E.</creatorcontrib><creatorcontrib>Stamatatos, E.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kavallieratou, E.</au><au>Stamatatos, E.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Improving the quality of degraded document images</atitle><btitle>Second International Conference on Document Image Analysis for Libraries (DIAL'06)</btitle><stitle>DIAL</stitle><date>2006</date><risdate>2006</risdate><spage>10 pp.</spage><epage>349</epage><pages>10 pp.-349</pages><isbn>0769525318</isbn><isbn>9780769525310</isbn><abstract>It is common for libraries to provide public access to historical and ancient document image collections. It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarization approach for improving the quality of old documents using a combination of global and local thresholding. First, a global thresholding technique specifically designed for old document images is applied to the entire image. Then, the image areas that still contain background noise are detected and the same technique is re-applied to each area separately. Hence, we achieve better adaptability of the algorithm in cases where various kinds of noise coexist in different areas of the same image while avoiding the computational and time cost of applying a local thresholding in the entire image. Evaluation results based on a collection of historical document images indicate that the proposed approach is effective in removing background noise and improving the quality of degraded documents while documents already in good condition are not affected</abstract><pub>IEEE</pub><doi>10.1109/DIAL.2006.23</doi></addata></record> |
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subjects | Background noise Capacitive sensors Computational efficiency Cultural differences Degradation Image analysis Lighting Pixel Software libraries Systems engineering and theory |
title | Improving the quality of degraded document images |
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