Visibility classification of pellets in piles for sizing without overlapped particle error
2008 (English)In: 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications: DICTA 2007 ; 3 - 5 Dec. 2007, Glenelg, [Adelaide], South Australia ; pPiscataway, NJ oceedings / [ed] Murk J. Bottema, IEEE Communications Society, 2008, 508-514 p.Conference paper (Refereed)
Size measurement of pellets in industry is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of pellet size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. We make a distinction between entirely visible and partially visible pellets. This is a significant distinction as the size of partially visible pellets cannot be correctly estimated with existing size measures and would bias any size estimate. Literature review indicates that other image analysis techniques fail to make this distinction. Statistical classification methods are used to discriminate pellets on the surface of a pile between entirely visible and partially visible pellets. Size estimates of the surface of a pellet pile show that the overlapped particle error is overcome by only estimating the surface size distribution with entirely visible pellets.
Place, publisher, year, edition, pages
IEEE Communications Society, 2008. 508-514 p.
Research subject Signal Processing
IdentifiersURN: urn:nbn:se:ltu:diva-37456DOI: 10.1109/DICTA.2007.4426839Local ID: b7e7f3c0-6a72-11dc-9e58-000ea68e967bISBN: 978-1-424-43161-8OAI: oai:DiVA.org:ltu-37456DiVA: diva2:1010954
Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications : 03/12/2007 - 05/12/2007
Projects3D Mätning Projekt
Godkänd; 2008; 20070924 (tobiasa)2016-10-032016-10-03Bibliographically approved