| dc.rights.license | Visos teisės saugomos / All rights reserved | en_US |
| dc.contributor.author | Tumas, Paulius | |
| dc.contributor.author | Serackis, Artūras | |
| dc.date.accessioned | 2025-12-04T12:11:05Z | |
| dc.date.available | 2025-12-04T12:11:05Z | |
| dc.date.issued | 2017 | |
| dc.identifier.isbn | 9781538639993 | en_US |
| dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/159482 | |
| dc.description.abstract | Computer vision-based image analysis is one of the most widely used food quality tool in food industry. It allows to perform the non-contact and low-cost measurements of inspected object's surface and color. The aim of investigation presented in this paper is to propose an effective algorithm for background subtraction on multi-spectral images. Paper presents the application of multi-spectral image analysis approach using near infrared low cost camera and four different key wavelengths for controlled LED illumination. The performance of the background subtraction algorithm was measured by comparing the variation of estimated area of the food samples in the foreground. An experimental tests showed, that the best performance of background subtraction is received using infrared LED illumination with key wavelength of 940nm using all methods selected for comparison. | en_US |
| dc.format.extent | 4 p. | en_US |
| dc.format.medium | Tekstas / Text | en_US |
| dc.language.iso | en | en_US |
| dc.relation.uri | https://etalpykla.vilniustech.lt/handle/123456789/159383 | en_US |
| dc.source.uri | https://ieeexplore.ieee.org/document/7950322 | en_US |
| dc.subject | Raspberry Pi | en_US |
| dc.subject | NoIRv2 camera | en_US |
| dc.subject | near-infrared | en_US |
| dc.subject | food inspection | en_US |
| dc.subject | multi-spectral imaging | en_US |
| dc.subject | low-cost camera | en_US |
| dc.subject | contour extraction | en_US |
| dc.subject | food quality | en_US |
| dc.title | Effective background subtraction algorithm for food inspection using a low-cost near infrared camera | en_US |
| dc.type | Konferencijos publikacija / Conference paper | en_US |
| dcterms.accrualMethod | Rankinis pateikimas / Manual submission | en_US |
| dcterms.issued | 2017-06-19 | |
| dcterms.references | 16 | en_US |
| dc.description.version | Taip / Yes | en_US |
| dc.contributor.institution | Vilniaus Gedimino technikos universitetas | en_US |
| dc.contributor.institution | Vilnius Gediminas Technical University | en_US |
| dc.contributor.department | Elektroninių sistemų katedra / Department of Electronic Systems | en_US |
| dcterms.sourcetitle | 2017 Open Conference of Electrical, Electronic and Information Sciences (eStream), April 27, 2017, Vilnius, Lithuania | en_US |
| dc.identifier.eisbn | 9781538639986 | en_US |
| dc.publisher.name | IEEE | en_US |
| dc.publisher.country | United States of America | en_US |
| dc.publisher.city | New York | en_US |
| dc.identifier.doi | https://doi.org/10.1109/eStream.2017.7950322 | en_US |