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231223s1995 xx ||||| 00| ||eng c |
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|a (DE-627)NLM177764007
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|a (NLM)18290036
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Yhann, S R
|e verfasserin
|4 aut
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| 245 |
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|a Boundary localization in texture segmentation
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| 264 |
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|c 1995
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 02.10.2012
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| 500 |
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|a Date Revised 21.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Localizing boundaries between textured image regions without sacrificing the labeling accuracy of interior regions remains a problem in segmentation. Difficulties arise because of the conflicting requirements of localization and labeling. Boundary localization usually demands observing the features over small neighborhoods, whereas labeling accuracy increases with the size of the observation neighborhood. This problem is further exacerbated in texture segmentation by the spatially distributed nature of texture features. In this correspondence, we develop a multiresolution approach that combines localized and distributed features to directly address boundary localization in texture segmentation. Maximum localization is achieved by using the gray-level discontinuities at the boundary between textures to define the boundary. The properties that characterize the gray-level discontinuity at texture boundaries are developed and an algorithm is designed to localize the boundary using these discontinuities. This segmentation algorithm is implemented and successfully tested on a set of Brodatz texture mosaics and AVHRR satellite imagery
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|a Journal Article
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|a Young, T Y
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 4(1995), 6 vom: 15., Seite 849-56
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
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|g volume:4
|g year:1995
|g number:6
|g day:15
|g pages:849-56
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|d 4
|j 1995
|e 6
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|h 849-56
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