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008			150903s2008 xxk| o |||| 0|eng d
020			_a9781846289132 _99781846289132
024	7		_a10.1007/9781846289132 _2doi
035			_avtls000344077
039		9	_a201509030406 _bVLOAD _c201405050302 _dVLOAD _y201402061247 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTA1637-1638
100	1		_aArmstrong, Brian S.R. _eautor _9323285
245	1	0	_aPrecision Landmark Location for Machine Vision and Photogrammetry : _bFinding and Achieving the Maximum Possible Accuracy / _cby Brian S.R. Armstrong, José A. Gutierrez.
264		1	_aLondon : _bSpringer London, _c2008.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aPhysics of Digital Image Formation -- Analytic Framework for Landmark Location Uncertainty -- Model-based Landmark Location Estimators -- Two-dimensional Noncollocated Numerical Integration -- Computational Tools -- Experimental Validation -- Studies of Landmark Location Uncertainty -- Conclusions.
520			_aThe applications of image-based measurement are many and various: image-guided surgery, mobile-robot navigation, component alignment, part inspection and photogrammetry, among others. In all these applications, landmarks are detected and located in images, and measurements made from those locations. Precision Landmark Location for Machine Vision and Photogrammetry addresses the ubiquitous problem of measurement error associated with determining the location of landmarks in images. With a detailed model of the image formation process and landmark location estimation, the Cramér–Rao Lower Bound (CRLB) theory of statistics is applied to determine the least possible measurement uncertainty in a given situation. This monograph provides the reader with: • the most complete treatment to date of precision landmark location and the engineering aspects of image capture and processing; • detailed theoretical treatment of the CRLB; • a software tool for analyzing the potential performance-specific camera/lens/algorithm configurations; • two novel algorithms which achieve precision very close to the CRLB; • an experimental method for determining the accuracy of landmark location; • downloadable MATLAB® package to assist the reader with applying theoretically-derived results to practical engineering configurations. All of this adds up to a treatment that is at once theoretically sound and eminently practical. Precision Landmark Location for Machine Vision and Photogrammetry will be of great interest to computer scientists and engineers working with and/or studying image processing and measurement. It includes cutting-edge theoretical developments and practical tools so it will appeal to research investigators and system designers.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aGutierrez, José A. _eautor _9323286
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781846289125
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-84628-913-2 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c291827 _d291827