Machine Vision Methods for the Grading of Crushed Aggregate

Xiaoyu Qiao, Fionn Murtagh, Danny Crookes, Paul Walsh, P. A.Muhammed Basheer, Adrian Long

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We address the problems of (i) segmenting coarse from fine granularity materials, and (ii) discriminating between materials of different granularities. For the former we use wavelet features, and an enhanced version of the widely used EM algorithm. A weighted Gaussian mixture model is used, with a second order spatial neighborhood. For granularity discrimination we investigate the use of multiresolution entropy. We illustrate the good results obtained with a number of practical cases.

Original languageEnglish
Title of host publicationOpto-Ireland 2002
Subtitle of host publicationOptical Metrology, Imaging, and Machine Vision
EditorsAndrew Shearer, Fionn D. Murtagh, James Mahon, Paul F. Whelan
PublisherSPIE
Pages264-270
Number of pages7
Volume4877
ISBN (Print)0819446580, 9780819446589
DOIs
Publication statusPublished - 19 Mar 2003
Externally publishedYes
EventOpto-Ireland 2002: Optical metrology, Imaging, and Machine Vision - Galway, Ireland
Duration: 5 Sep 20026 Sep 2002
https://www.researchgate.net/publication/260899755_Opto-Ireland_2002_Optical_Metrology_Imaging_and_Machine_Vision

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Volume4877
ISSN (Print)0277-786X

Conference

ConferenceOpto-Ireland 2002: Optical metrology, Imaging, and Machine Vision
CountryIreland
CityGalway
Period5/09/026/09/02
Internet address

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Cite this

Qiao, X., Murtagh, F., Crookes, D., Walsh, P., Basheer, P. A. M., & Long, A. (2003). Machine Vision Methods for the Grading of Crushed Aggregate. In A. Shearer, F. D. Murtagh, J. Mahon, & P. F. Whelan (Eds.), Opto-Ireland 2002: Optical Metrology, Imaging, and Machine Vision (Vol. 4877, pp. 264-270). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 4877). SPIE. https://doi.org/10.1117/12.467440