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231223s1995 xx ||||| 00| ||eng c |
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|a pubmed24n0593.xml
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|a (DE-627)NLM177782625
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|a (NLM)18291995
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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 Tretter, D
|e verfasserin
|4 aut
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| 245 |
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|a A multiscale stochastic image model for automated inspection
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|c 1995
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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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|a Date Revised 22.02.2008
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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 We develop a novel multiscale stochastic image model to describe the appearance of a complex three-dimensional object in a two-dimensional monochrome image. This formal image model is used in conjunction with Bayesian estimation techniques to perform automated inspection. The model is based on a stochastic tree structure in which each node is an important subassembly of the three-dimensional object. The data associated with each node or subassembly is modeled in a wavelet domain. We use a fast multiscale search technique to compute the sequential MAP (SMAP) estimate of the unknown position, scale factor, and 2-D rotation for each subassembly. The search is carried out in a manner similar to a sequential likelihood ratio test, where the process advances in scale rather than time. The results of this search determine whether or not the object passes inspection. A similar search is used in conjunction with the EM algorithm to estimate the model parameters for a given object from a set of training images. The performance of the algorithm is demonstrated on two different real assemblies
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|a Journal Article
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|a Bouman, C A
|e verfasserin
|4 aut
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|a Khawaja, K W
|e verfasserin
|4 aut
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| 700 |
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|a Maciejewski, A A
|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), 12 vom: 15., Seite 1641-54
|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:12
|g day:15
|g pages:1641-54
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|a AR
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|d 4
|j 1995
|e 12
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|h 1641-54
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