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Depth estimation using multiwavelet analysis based stereo vision approach

Bhatti, Asim and Nahavandi, Saeid 2008, Depth estimation using multiwavelet analysis based stereo vision approach, International journal of wavelets, multiresolution and information processing, vol. 6, no. 3, pp. 481-497.

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Title Depth estimation using multiwavelet analysis based stereo vision approach
Author(s) Bhatti, AsimORCID iD for Bhatti, Asim orcid.org/0000-0001-6876-1437
Nahavandi, Saeid
Journal name International journal of wavelets, multiresolution and information processing
Volume number 6
Issue number 3
Start page 481
End page 497
Total pages 17
Publisher World Scientific
Place of publication New Jersey
Publication date 2008-05
ISSN 0219-6913
1793-690X
Keyword(s) 3D depth estimation
disparity estimation
multiwavelets transform modulus maxima
stereo vision
Summary The problem of dimensional defects in aluminum die-casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo camera pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.
Language eng
Field of Research 080104 Computer Vision
Socio Economic Objective 890299 Computer Software and Services not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2008
Copyright notice ©2008, World Scientific Publishing
Persistent URL http://hdl.handle.net/10536/DRO/DU:30017986

Document type: Journal Article
Collection: School of Engineering and Information Technology
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