A generic implementation framework for stereo matching algorithms


Autoria(s): Banks, Jasmine; Porter, Reid; Bennamoun, Mohammed; Corke, Peter
Contribuinte(s)

Chaplin, Bob I.

Page, Wyatt H.

Data(s)

10/12/1997

Resumo

Traditional area-based matching techniques make use of similarity metrics such as the Sum of Absolute Differences(SAD), Sum of Squared Differences (SSD) and Normalised Cross Correlation (NCC). Non-parametric matching algorithms such as the rank and census rely on the relative ordering of pixel values rather than the pixels themselves as a similarity measure. Both traditional area-based and non-parametric stereo matching techniques have an algorithmic structure which is amenable to fast hardware realisation. This investigation undertakes a performance assessment of these two families of algorithms for robustness to radiometric distortion and random noise. A generic implementation framework is presented for the stereo matching problem and the relative hardware requirements for the various metrics investigated.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/55371/

Publicador

The Department of Production Technology, Massey University

Relação

http://eprints.qut.edu.au/55371/1/dicta.pdf

Banks, Jasmine, Porter, Reid, Bennamoun, Mohammed, & Corke, Peter (1997) A generic implementation framework for stereo matching algorithms. In Chaplin, Bob I. & Page, Wyatt H. (Eds.) DICTA'97 and IVCNZ'97 Conference Proceedings, The Department of Production Technology, Massey University, Auckland, New Zealand, pp. 29-34.

Direitos

Copyright 1997 [please consult the author]

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080104 Computer Vision #080106 Image Processing #090601 Circuits and Systems #stereo vision #image matching #area-based matching #rank transform #census transform #hardware implementation
Tipo

Conference Paper