Wood Recognition and Quality Imaging Inspection Systems

Joint Authors

Kryl, Martin
Danys, Lukas
Jaros, Rene
Martinek, Radek
Kodytek, Pavel
Bilik, Petr

Source

Journal of Sensors

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-19, 19 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-09-17

Country of Publication

Egypt

No. of Pages

19

Main Subjects

Civil Engineering

Abstract EN

Forestry is an undoubtedly crucial part of today’s industry; thus, automation of certain visual tasks could lead to a significant increase in productivity and reduction of labor costs.

Eye fatigue or lack of attention during manual visual inspections can lead to falsely categorized wood, thus leading to major loss of earnings.

These mistakes could be eliminated using automated vision inspection systems.

This article focuses on the comparison of researched methodologies related to wood type classification and wood defect detection/identification; hence, readers with an intention of building a similar vision-based system have summarized review to build upon.

American Psychological Association (APA)

Kryl, Martin& Danys, Lukas& Jaros, Rene& Martinek, Radek& Kodytek, Pavel& Bilik, Petr. 2020. Wood Recognition and Quality Imaging Inspection Systems. Journal of Sensors،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1190397

Modern Language Association (MLA)

Kryl, Martin…[et al.]. Wood Recognition and Quality Imaging Inspection Systems. Journal of Sensors No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1190397

American Medical Association (AMA)

Kryl, Martin& Danys, Lukas& Jaros, Rene& Martinek, Radek& Kodytek, Pavel& Bilik, Petr. Wood Recognition and Quality Imaging Inspection Systems. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1190397

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1190397