Erosion band signatures for spatial extraction of features
We introduce Erosion Band Signatures (EBS), which are a codification of the spatial coherence of features extracted from a region. This coherence is often lost in traditional global and local feature extraction methods, thereby diminishing a feature’s discriminative strength. The erosion band signat...
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Veröffentlicht in: | Machine vision and applications 2013-05, Vol.24 (4), p.695-705 |
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creator | Vazquez, Eduard Yang, Xiaoyun Slabaugh, Greg |
description | We introduce
Erosion Band Signatures
(EBS), which are a codification of the spatial coherence of features extracted from a region. This coherence is often lost in traditional global and local feature extraction methods, thereby diminishing a feature’s discriminative strength. The erosion band signature is generated through iterative erosions of the region of interest, forming what we call
erosion bands
. Features are then extracted from each band and accumulated in a specific order to form the EB signature, which preserves spatial information of the features. To demonstrate the versatility of EBS, we have implemented the method in two very different applications: polyp detection and region-based head tracking. In polyp detection, EBS provides an effective way to characterize spatial differences between the perimeter and core of a polyp candidate, and improves a state-of-the-art computer-aided detection method with an improved 27.6% reduction of false positives. We also apply EBS analysis to region-based tracking yielding a very clear improvement in both robustness and accuracy. |
doi_str_mv | 10.1007/s00138-012-0422-8 |
format | Article |
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Erosion Band Signatures
(EBS), which are a codification of the spatial coherence of features extracted from a region. This coherence is often lost in traditional global and local feature extraction methods, thereby diminishing a feature’s discriminative strength. The erosion band signature is generated through iterative erosions of the region of interest, forming what we call
erosion bands
. Features are then extracted from each band and accumulated in a specific order to form the EB signature, which preserves spatial information of the features. To demonstrate the versatility of EBS, we have implemented the method in two very different applications: polyp detection and region-based head tracking. In polyp detection, EBS provides an effective way to characterize spatial differences between the perimeter and core of a polyp candidate, and improves a state-of-the-art computer-aided detection method with an improved 27.6% reduction of false positives. We also apply EBS analysis to region-based tracking yielding a very clear improvement in both robustness and accuracy.</description><identifier>ISSN: 0932-8092</identifier><identifier>EISSN: 1432-1769</identifier><identifier>DOI: 10.1007/s00138-012-0422-8</identifier><identifier>CODEN: MVAPEO</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Applied sciences ; Artificial intelligence ; Codification ; Coherence ; Communications Engineering ; Computer Science ; Computer science; control theory; systems ; Data processing. List processing. Character string processing ; Erosion ; Exact sciences and technology ; Extraction ; Feature extraction ; Image Processing and Computer Vision ; Iterative methods ; Memory organisation. Data processing ; Networks ; Original Paper ; Pattern Recognition ; Pattern recognition. Digital image processing. Computational geometry ; Preserves ; Reduction ; Signatures ; Software ; Spatial data ; Tracking ; Vision systems</subject><ispartof>Machine vision and applications, 2013-05, Vol.24 (4), p.695-705</ispartof><rights>Springer-Verlag 2012</rights><rights>2014 INIST-CNRS</rights><rights>Machine Vision and Applications is a copyright of Springer, (2012). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c379t-2d2ee33489e37f66213bbc8949c370d3a2668ab7e82d275754baa1370a29ef853</citedby><cites>FETCH-LOGICAL-c379t-2d2ee33489e37f66213bbc8949c370d3a2668ab7e82d275754baa1370a29ef853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00138-012-0422-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00138-012-0422-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27618326$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Vazquez, Eduard</creatorcontrib><creatorcontrib>Yang, Xiaoyun</creatorcontrib><creatorcontrib>Slabaugh, Greg</creatorcontrib><title>Erosion band signatures for spatial extraction of features</title><title>Machine vision and applications</title><addtitle>Machine Vision and Applications</addtitle><description>We introduce
Erosion Band Signatures
(EBS), which are a codification of the spatial coherence of features extracted from a region. This coherence is often lost in traditional global and local feature extraction methods, thereby diminishing a feature’s discriminative strength. The erosion band signature is generated through iterative erosions of the region of interest, forming what we call
erosion bands
. Features are then extracted from each band and accumulated in a specific order to form the EB signature, which preserves spatial information of the features. To demonstrate the versatility of EBS, we have implemented the method in two very different applications: polyp detection and region-based head tracking. In polyp detection, EBS provides an effective way to characterize spatial differences between the perimeter and core of a polyp candidate, and improves a state-of-the-art computer-aided detection method with an improved 27.6% reduction of false positives. We also apply EBS analysis to region-based tracking yielding a very clear improvement in both robustness and accuracy.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Codification</subject><subject>Coherence</subject><subject>Communications Engineering</subject><subject>Computer Science</subject><subject>Computer science; control theory; systems</subject><subject>Data processing. List processing. Character string processing</subject><subject>Erosion</subject><subject>Exact sciences and technology</subject><subject>Extraction</subject><subject>Feature extraction</subject><subject>Image Processing and Computer Vision</subject><subject>Iterative methods</subject><subject>Memory organisation. Data processing</subject><subject>Networks</subject><subject>Original Paper</subject><subject>Pattern Recognition</subject><subject>Pattern recognition. Digital image processing. 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Erosion Band Signatures
(EBS), which are a codification of the spatial coherence of features extracted from a region. This coherence is often lost in traditional global and local feature extraction methods, thereby diminishing a feature’s discriminative strength. The erosion band signature is generated through iterative erosions of the region of interest, forming what we call
erosion bands
. Features are then extracted from each band and accumulated in a specific order to form the EB signature, which preserves spatial information of the features. To demonstrate the versatility of EBS, we have implemented the method in two very different applications: polyp detection and region-based head tracking. In polyp detection, EBS provides an effective way to characterize spatial differences between the perimeter and core of a polyp candidate, and improves a state-of-the-art computer-aided detection method with an improved 27.6% reduction of false positives. We also apply EBS analysis to region-based tracking yielding a very clear improvement in both robustness and accuracy.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s00138-012-0422-8</doi><tpages>11</tpages></addata></record> |
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subjects | Applied sciences Artificial intelligence Codification Coherence Communications Engineering Computer Science Computer science control theory systems Data processing. List processing. Character string processing Erosion Exact sciences and technology Extraction Feature extraction Image Processing and Computer Vision Iterative methods Memory organisation. Data processing Networks Original Paper Pattern Recognition Pattern recognition. Digital image processing. Computational geometry Preserves Reduction Signatures Software Spatial data Tracking Vision systems |
title | Erosion band signatures for spatial extraction of features |
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