An image processing method to recognize position of sawn boards within the log

DOI

This dataset includes source images, codes, and results used in a paper that addresses the problem of timber board positioning within the log they were sawn from. The method takes as input images of the end cross-section of logs and boards that can be obtained in a sawmill. It uses a two-step image matching method based on scale invariant feature transform (SIFT) and normalized correlation coefficient (NCC). In the first step, the scale factor and rotation angle of board end images are estimated from the board images that are correctly identified on the log end image by SIFT. Then, the accurate position of each board within the log end image is achieved by the NCC method. The method has been tested on 70 different log images and the 798 corresponding board images of various visual aspects and coming from three different species (Douglas fir, Norway spruce, and oak). The results fully demonstrate that the proposed method is not only rotation and scale invariant, but also has high accuracy properties.

Identifier
DOI https://doi.org/10.57745/XCVQSG
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/XCVQSG
Provenance
Creator LI, Xiaolin ORCID logo; POT, Guillaume (ORCID: 0000-0001-9751-251X); NGO, Phuc ORCID logo; VIGUIER, Joffrey (ORCID: 0000-0001-7926-599X); PENVERN, Hélène ORCID logo
Publisher Recherche Data Gouv
Contributor LI, Xiaolin; POT, Guillaume; Arts et Métiers Sciences & Technologies (LaBoMaP); Laboratoire lorrain de Recherche en Informatique et ses Applications; Entrepôt-Catalogue Recherche Data Gouv
Publication Year 2023
Funding Reference ANR ANR‐21‐CE10‐0002‐01
Rights etalab 2.0; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/etalab-2.0.html
OpenAccess true
Contact LI, Xiaolin (Ecole Nationale Supérieure d'Arts et Métiers - MFA); POT, Guillaume (Ecole Nationale Supérieure d'Arts et Métiers - MFA)
Representation
Resource Type Dataset
Format application/zip; text/x-python; text/plain; text/tab-separated-values
Size 384252; 334875830; 2034332278; 4306; 17656; 1268; 5157; 44433; 1185833077
Version 1.4
Discipline Agriculture, Forestry, Horticulture; Computer Science; Engineering Sciences; Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Construction Engineering and Architecture; Engineering; Life Sciences
Spatial Coverage Arts et Métiers Campus de Cluny