000 | 03254nam a22005415i 4500 | ||
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001 | 978-3-540-47287-2 | ||
003 | DE-He213 | ||
005 | 20160624102022.0 | ||
007 | cr nn 008mamaa | ||
008 | 121227s1992 gw | s |||| 0|eng d | ||
020 |
_a9783540472872 _9978-3-540-47287-2 |
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024 | 7 |
_a10.1007/3-540-55798-9 _2doi |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTJ210.2-211.495 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aTJFM1 _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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082 | 0 | 4 |
_a006.3 _223 |
245 | 1 | 0 |
_aRelational Matching _h[electronic resource] / _cedited by G. Vosselman. |
260 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c1992. |
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264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c1992. |
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300 |
_aX, 18 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v628 |
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505 | 0 | _aComputer vision and matching -- A classification of matching methods -- Formal description of relational matching -- Problem definition and contributions of the thesis -- Information theory:Selected Topics -- Evaluation of mappings between relational descriptions -- Tree search methods and heuristics -- Relational image and model description -- Evaluation functions for object location -- Strategy and performance of the tree search for object location -- Summary and discussion. | |
520 | _aRelational matching is a method for finding the best correspondences betweenstructural descriptions. It is widely used in computer vision for the recognition and location of objects in digital images. For this purpose, the digital images and the object models are represented by structural descriptions. The matching algorithm then has to determine which image elements and object model parts correspond. This book is the result of abasic study of relational matching. The book focuses particularly on the evaluation of correspondences. In order to find the best match, one needs a measure to evaluate the quality of a match. The author reviews the evaluation measures that have been suggested over the past few decades and presents a new measure based on information theory. The resulting theorycombines matching strategies, information theory, and tree search methods. For the benefit of the reader, comprehensive introductions are given to all these topics. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aSoftware engineering. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aOptical pattern recognition. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aPattern Recognition. |
650 | 2 | 4 | _aModels and Principles. |
650 | 2 | 4 | _aSoftware Engineering/Programming and Operating Systems. |
700 | 1 |
_aVosselman, G. _eeditor. |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540557982 |
786 | _dSpringer | ||
830 | 0 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v628 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/3-540-55798-9 |
942 |
_2EBK6039 _cEBK |
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999 |
_c35333 _d35333 |