Recognition of boards using wood fingerprints based on a fusion of feature detection methods
2015 (English)In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 111, 164-173 p.Article in journal (Refereed) Published
This paper investigates the possibility to automatically match and recognize individual Scots pine (Pinus sylvestris L.) boards using a fusion of two feature detection methods. The first method denoted Block matching method, detects corners and matches square regions around these corners using a normalized Sum of Squared Differences (SSD) measure. The second method denoted the SURF (Speeded-Up Robust Features) matching method, matches SURF features between images (Bay et al., 2008). The fusion of the two feature detection methods improved the recognition rate of wooden floorboards substantially compared to the individual methods. Perfect matching accuracy was obtained for board pieces with more than 20 knots using high quality images. More than 90% matching accuracy was achieved for board pieces with more than 10 knots, using both high- and low quality images.
Place, publisher, year, edition, pages
2015. Vol. 111, 164-173 p.
Research subject Wood Technology; Signal Processing
IdentifiersURN: urn:nbn:se:ltu:diva-3568DOI: 10.1016/j.compag.2014.12.014Local ID: 16587b6c-231a-417c-a13c-834c3944a9f3OAI: oai:DiVA.org:ltu-3568DiVA: diva2:976426
Validerad; 2015; Nivå 2; 20150122 (tobpah)2016-09-292016-09-29Bibliographically approved