Depth estimation using multi-wavelet analysis based stereo vision approach Bhatti, Asim and Nahavandi, Saeid 2007, Depth estimation using multi-wavelet analysis based stereo vision approach, in Wavelet analysis and pattern recognition, IEEE Xplore, Piscataway, N.J., pp. 1471-1476. Attached Files Name Description MIMEType Size Downloads nahavandi-depthestimation-2007.pdf Published version application/pdf 916.24KB 231 Title Depth estimation using multi-wavelet analysis based stereo vision approach Author(s) Bhatti, Asim orcid.org/0000-0001-6876-1437 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name International Conference on Wavelet Analysis and Pattern Recognition (2007: Beijing, China) Conference location Beijing, China Conference dates 2-4 November 2007 Title of proceedings Wavelet analysis and pattern recognition Editor(s) Institute of Electrical and Electronics Engineers (IEEE) Publication date 2007 Conference series International Conference on Wavelet Analysis and Pattern Recognition Start page 1471 End page 1476 Publisher IEEE Xplore Place of publication Piscataway, N.J. 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 cameras 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. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 1424410657 9781424410651 Language eng Field of Research 080106 Image Processing Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1 Full written paper - refereed Copyright notice ©2007, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30008196 Document type: Conference Paper Collections: School of Engineering and Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 10 Mar 2009, 14:18:23 EST Wed, 25 Aug 2010, 14:27:15 EST Thu, 09 Sep 2010, 09:22:46 EST Fri, 16 Mar 2012, 16:33:05 EST Mon, 09 Jun 2014, 11:03:49 EST Wed, 27 Aug 2014, 21:38:38 EST Wed, 21 Oct 2015, 13:23:19 EST Wed, 21 Oct 2015, 16:39:04 EST Tue, 06 Sep 2016, 10:59:53 EST Tue, 05 Dec 2017, 06:22:06 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 782 Abstract Views, 249 File Downloads  -  Detailed Statistics Created: Mon, 29 Sep 2008, 09:05:41 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.