Inclusion filters: a class of self-dual connected operators
In this paper, we define a connected operator that either fills or retains the holes of the connected sets depending on application-specific criteria that are increasing in the set theoretic sense. We refer to this class of connected operators as inclusion filters, which are shown to be increasing,...
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| Veröffentlicht in: | IEEE transactions on image processing 2005-11, Vol.14 (11), p.1736-1746 |
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| container_title | IEEE transactions on image processing |
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| creator | Ray, N. Acton, S.T. |
| description | In this paper, we define a connected operator that either fills or retains the holes of the connected sets depending on application-specific criteria that are increasing in the set theoretic sense. We refer to this class of connected operators as inclusion filters, which are shown to be increasing, idempotent, and self dual (gray-level inversion invariance). We demonstrate self duality for 8-adjacency on a discrete Cartesian grid. Inclusion filters are defined first for binary-valued images, and then the definition is extended to grayscale imagery. It is also shown that inclusion filters are levelings, a larger class of connected operators. Several important applications of inclusion filters are demonstrated-automatic segmentation of the lung cavities from magnetic resonance imagery, user interactive shape delineation in content-based image retrieval, registration of intravital microscopic video sequences, and detection and tracking of cells from these sequences. The numerical performance measures on 100-cell tracking experiments show that the use of inclusion filter improves the total number of frames successfully tracked by five times and provides a threefold reduction in the overall position error. |
| doi_str_mv | 10.1109/TIP.2005.857251 |
| format | Article |
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(IEEE) 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c403t-1128ca6f490fb70f5d4c08a1696a8d6e8279cd7b812040b9710fe242a092b67c3</citedby><cites>FETCH-LOGICAL-c403t-1128ca6f490fb70f5d4c08a1696a8d6e8279cd7b812040b9710fe242a092b67c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1518939$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27923,27924,54757</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1518939$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17229470$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16279174$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ray, N.</creatorcontrib><creatorcontrib>Acton, S.T.</creatorcontrib><title>Inclusion filters: a class of self-dual connected operators</title><title>IEEE transactions on image processing</title><addtitle>TIP</addtitle><addtitle>IEEE Trans Image Process</addtitle><description>In this paper, we define a connected operator that either fills or retains the holes of the connected sets depending on application-specific criteria that are increasing in the set theoretic sense. 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The numerical performance measures on 100-cell tracking experiments show that the use of inclusion filter improves the total number of frames successfully tracked by five times and provides a threefold reduction in the overall position error.</description><subject>Adjacency tree</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Artificial Intelligence</subject><subject>connected operator</subject><subject>Content based retrieval</subject><subject>Exact sciences and technology</subject><subject>Filters</subject><subject>Gray-scale</subject><subject>Image Enhancement - methods</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image processing</subject><subject>Image retrieval</subject><subject>Image segmentation</subject><subject>Information Storage and Retrieval - methods</subject><subject>Information theory</subject><subject>Information, signal and communications theory</subject><subject>level sets</subject><subject>Lungs</subject><subject>Magnetic force microscopy</subject><subject>Magnetic resonance</subject><subject>Magnetic separation</subject><subject>Microscopy, Video - methods</subject><subject>Numerical Analysis, Computer-Assisted</subject><subject>self duality</subject><subject>Shape</subject><subject>Signal processing</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Studies</subject><subject>Subtraction Technique</subject><subject>Telecommunications and information theory</subject><issn>1057-7149</issn><issn>1941-0042</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqFkMtLxDAQh4Movs8eBCmC3rrOpGkeehLxsSDoQc8hTROoZJs1aQ_-93bZhQUvnjKQb34z8xFyhjBDBHXzMX-fUYB6JmtBa9whh6gYlgCM7k411KIUyNQBOcr5CwBZjXyfHCCnQqFgh-Ru3tsw5i72he_C4FK-LUxhg8m5iL7ILviyHU0obOx7ZwfXFnHpkhliyidkz5uQ3enmPSafT48fDy_l69vz_OH-tbQMqqFEpNIa7pkC3wjwdcssSINccSNb7uS0i21FI5ECg0YJBO8oowYUbbiw1TG5XucuU_weXR70osvWhWB6F8esuRRCsgr-BakEDpxWE3j5B_yKY-qnI7SUFUPk9SrtZg3ZFHNOzutl6hYm_WgEvbKvJ_t6ZV-v7U8dF5vYsVm4dstvdE_A1QYw2Zrgk-ltl7ecoFQxsRp9vuY659z2u0apKlX9Aq9Akrs</recordid><startdate>20051101</startdate><enddate>20051101</enddate><creator>Ray, N.</creator><creator>Acton, S.T.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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We refer to this class of connected operators as inclusion filters, which are shown to be increasing, idempotent, and self dual (gray-level inversion invariance). We demonstrate self duality for 8-adjacency on a discrete Cartesian grid. Inclusion filters are defined first for binary-valued images, and then the definition is extended to grayscale imagery. It is also shown that inclusion filters are levelings, a larger class of connected operators. Several important applications of inclusion filters are demonstrated-automatic segmentation of the lung cavities from magnetic resonance imagery, user interactive shape delineation in content-based image retrieval, registration of intravital microscopic video sequences, and detection and tracking of cells from these sequences. The numerical performance measures on 100-cell tracking experiments show that the use of inclusion filter improves the total number of frames successfully tracked by five times and provides a threefold reduction in the overall position error.</abstract><cop>New York, NY</cop><pub>IEEE</pub><pmid>16279174</pmid><doi>10.1109/TIP.2005.857251</doi><tpages>11</tpages></addata></record> |
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| subjects | Adjacency tree Algorithms Applied sciences Artificial Intelligence connected operator Content based retrieval Exact sciences and technology Filters Gray-scale Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Image retrieval Image segmentation Information Storage and Retrieval - methods Information theory Information, signal and communications theory level sets Lungs Magnetic force microscopy Magnetic resonance Magnetic separation Microscopy, Video - methods Numerical Analysis, Computer-Assisted self duality Shape Signal processing Signal Processing, Computer-Assisted Studies Subtraction Technique Telecommunications and information theory |
| title | Inclusion filters: a class of self-dual connected operators |
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