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Skeletonizing by compressed line adjacency graph in two directions
Now all the block based skeletonizing algorithms only use the compressed line adjacency graph scanned in one direction. For lines approximately parallel to the scan direction, there is difficulty extracting the skeleton because such a line may be separated into several graph nodes or mixed with some...
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container_end_page | 20 vol.3 |
container_issue | |
container_start_page | 17 |
container_title | |
container_volume | 3 |
creator | Li Xingyuan Oh Weon-Geun Hong Jiarong |
description | Now all the block based skeletonizing algorithms only use the compressed line adjacency graph scanned in one direction. For lines approximately parallel to the scan direction, there is difficulty extracting the skeleton because such a line may be separated into several graph nodes or mixed with some pixels of other lines in the intersection point. In this paper, we propose a new skeletonizing method by combining c-LAG of horizontal and vertical direction. The main idea of the method is a rule for the skeletons in horizontal and vertical direction c-LAG and knowledge based node validation. The validation makes full use of global information in the image. It has been tested on a large amount of characters and high quality achieved. |
doi_str_mv | 10.1109/ICIP.1996.560358 |
format | conference_proceeding |
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For lines approximately parallel to the scan direction, there is difficulty extracting the skeleton because such a line may be separated into several graph nodes or mixed with some pixels of other lines in the intersection point. In this paper, we propose a new skeletonizing method by combining c-LAG of horizontal and vertical direction. The main idea of the method is a rule for the skeletons in horizontal and vertical direction c-LAG and knowledge based node validation. The validation makes full use of global information in the image. It has been tested on a large amount of characters and high quality achieved.</description><identifier>ISBN: 9780780332591</identifier><identifier>ISBN: 0780332598</identifier><identifier>DOI: 10.1109/ICIP.1996.560358</identifier><language>eng</language><publisher>IEEE</publisher><subject>Artificial intelligence ; Computer science ; Image coding ; Image segmentation ; Partitioning algorithms ; Pixel ; Skeleton ; Systems engineering and theory ; Testing ; Topology</subject><ispartof>Proceedings of 3rd IEEE International Conference on Image Processing, 1996, Vol.3, p.17-20 vol.3</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/560358$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/560358$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Li Xingyuan</creatorcontrib><creatorcontrib>Oh Weon-Geun</creatorcontrib><creatorcontrib>Hong Jiarong</creatorcontrib><title>Skeletonizing by compressed line adjacency graph in two directions</title><title>Proceedings of 3rd IEEE International Conference on Image Processing</title><addtitle>ICIP</addtitle><description>Now all the block based skeletonizing algorithms only use the compressed line adjacency graph scanned in one direction. For lines approximately parallel to the scan direction, there is difficulty extracting the skeleton because such a line may be separated into several graph nodes or mixed with some pixels of other lines in the intersection point. In this paper, we propose a new skeletonizing method by combining c-LAG of horizontal and vertical direction. The main idea of the method is a rule for the skeletons in horizontal and vertical direction c-LAG and knowledge based node validation. The validation makes full use of global information in the image. It has been tested on a large amount of characters and high quality achieved.</description><subject>Artificial intelligence</subject><subject>Computer science</subject><subject>Image coding</subject><subject>Image segmentation</subject><subject>Partitioning algorithms</subject><subject>Pixel</subject><subject>Skeleton</subject><subject>Systems engineering and theory</subject><subject>Testing</subject><subject>Topology</subject><isbn>9780780332591</isbn><isbn>0780332598</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1996</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj0tLw0AYRQdEUGr24mr-QOK8H0sNPgIFhdZ1mc58qVPTScgEJP56A-3lwoG7OHARuqekopTYx6ZuPitqraqkIlyaK1RYbchSzpm09AYVOR_JEiElM-QWPW9-oIOpT_EvpgPez9j3p2GEnCHgLibALhydh-RnfBjd8I1jwtNvj0McwU-xT_kOXbeuy1BcuEJfry_b-r1cf7w19dO6jJSIqXSBA3NMK089hMA1Z8SZlhhuKJPSC6blnhJuWwWq1YIqRoUQxhhh9bLzFXo4eyMA7IYxntw4785H-T_NrEeF</recordid><startdate>1996</startdate><enddate>1996</enddate><creator>Li Xingyuan</creator><creator>Oh Weon-Geun</creator><creator>Hong Jiarong</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1996</creationdate><title>Skeletonizing by compressed line adjacency graph in two directions</title><author>Li Xingyuan ; Oh Weon-Geun ; Hong Jiarong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i104t-ad3e2a276c1cedd37320a8f08381255c4275b1039f6e6f7416214448884971033</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Artificial intelligence</topic><topic>Computer science</topic><topic>Image coding</topic><topic>Image segmentation</topic><topic>Partitioning algorithms</topic><topic>Pixel</topic><topic>Skeleton</topic><topic>Systems engineering and theory</topic><topic>Testing</topic><topic>Topology</topic><toplevel>online_resources</toplevel><creatorcontrib>Li Xingyuan</creatorcontrib><creatorcontrib>Oh Weon-Geun</creatorcontrib><creatorcontrib>Hong Jiarong</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 Xplore</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>Li Xingyuan</au><au>Oh Weon-Geun</au><au>Hong Jiarong</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Skeletonizing by compressed line adjacency graph in two directions</atitle><btitle>Proceedings of 3rd IEEE International Conference on Image Processing</btitle><stitle>ICIP</stitle><date>1996</date><risdate>1996</risdate><volume>3</volume><spage>17</spage><epage>20 vol.3</epage><pages>17-20 vol.3</pages><isbn>9780780332591</isbn><isbn>0780332598</isbn><abstract>Now all the block based skeletonizing algorithms only use the compressed line adjacency graph scanned in one direction. For lines approximately parallel to the scan direction, there is difficulty extracting the skeleton because such a line may be separated into several graph nodes or mixed with some pixels of other lines in the intersection point. In this paper, we propose a new skeletonizing method by combining c-LAG of horizontal and vertical direction. The main idea of the method is a rule for the skeletons in horizontal and vertical direction c-LAG and knowledge based node validation. The validation makes full use of global information in the image. It has been tested on a large amount of characters and high quality achieved.</abstract><pub>IEEE</pub><doi>10.1109/ICIP.1996.560358</doi></addata></record> |
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identifier | ISBN: 9780780332591 |
ispartof | Proceedings of 3rd IEEE International Conference on Image Processing, 1996, Vol.3, p.17-20 vol.3 |
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language | eng |
recordid | cdi_ieee_primary_560358 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Artificial intelligence Computer science Image coding Image segmentation Partitioning algorithms Pixel Skeleton Systems engineering and theory Testing Topology |
title | Skeletonizing by compressed line adjacency graph in two directions |
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