Quantification of anatomical features in structural lumber using advanced imaging techniques
Faculty mentor/Supervisor
Lech Muszynski
Email Address
Department Affiliation
Wood Science & Engineering
Project Location
Richardson Hall, Corvallis Campus, but most of the work can be performed remotely
Project Description
Many mechanical properties of structural lumber used as laminations in mass timber composites are related to the anatomical structure of individual lumber pieces. Advanced visual strength grading of wood is based on such correlations.
The objective of this project is to record and analyze the anatomical characteristics of wood (e.g. annual ring count, early wood/latewood rates, presence, size and position of knots) on small (4 in x 4 in x 2 in) test samples harvested from graded structural lumber.
The approach is to use advanced imaging techniques (possibly supported by elements of artificial intelligence) to develop a rapid procedure for quantification of the anatomical characteristics of the samples (annual ring count, earlywood/latewood proportion, presence count position and sizes of knots). These characteristics will then be correlated with mechanical characteristics of these samples (measured ahead).
The intellectual input in the project may win the MEP student a lead or co-authorship of conference presentations and refereed publications of the outcomes of this project.
The objective of this project is to record and analyze the anatomical characteristics of wood (e.g. annual ring count, early wood/latewood rates, presence, size and position of knots) on small (4 in x 4 in x 2 in) test samples harvested from graded structural lumber.
The approach is to use advanced imaging techniques (possibly supported by elements of artificial intelligence) to develop a rapid procedure for quantification of the anatomical characteristics of the samples (annual ring count, earlywood/latewood proportion, presence count position and sizes of knots). These characteristics will then be correlated with mechanical characteristics of these samples (measured ahead).
The intellectual input in the project may win the MEP student a lead or co-authorship of conference presentations and refereed publications of the outcomes of this project.
Describe the type of work and tasks you anticipate the student will perform
The student is expected to:
1. collect high resolution images of four surfaces of the small specimens of graded structural lumber (4 in x 4 in x 4 in) [this activity may be outsourced id student works remotely)
2. prototype a image segmentation and feature quantification procedure in ImageJ or similar image analysis software package to identify features of interest and perform counting and measurements.
3. draft a script for rapid repetition of the procedure to process large batches of input image data
4. correlate the image analysis outputs with existing data on mechanical properties of the specimens
Bonus:
5. Conduct a limited state-of-the-art review on digital image segmentation of anatomical features in wood
6. Contribute as co-author in drafting conference presentations and/or refereed paper summarizing the outcomes
1. collect high resolution images of four surfaces of the small specimens of graded structural lumber (4 in x 4 in x 4 in) [this activity may be outsourced id student works remotely)
2. prototype a image segmentation and feature quantification procedure in ImageJ or similar image analysis software package to identify features of interest and perform counting and measurements.
3. draft a script for rapid repetition of the procedure to process large batches of input image data
4. correlate the image analysis outputs with existing data on mechanical properties of the specimens
Bonus:
5. Conduct a limited state-of-the-art review on digital image segmentation of anatomical features in wood
6. Contribute as co-author in drafting conference presentations and/or refereed paper summarizing the outcomes
Hourly rate of pay
$20
Certification
Yes
What is the expected timeline of this project?
The project is scheduled for Sep 15, 2025 to June 15, 2026 (Fall 2025, Winter and Spring 2026),. By average the work should take approximately 5 hours a week over 3x 10 term weeks (approximately 100-125 hours total).
Are special skills or knowledge required to work on this project?
No
Will training be provided?
Yes
How many hours per week do you anticipate a student to work?
5
How many hours per week do you anticipate engaging in direct mentorship?
by average, about 5 hours/week, though specific weekly timing may be flexible and depending on the MEP student academic schedule.
The plan is to set up a regular schedule of weekly training and progress update meetings during the school terms.
The MEP student will also be embedded in the larger research team meetings, both as contributor and observer.
Timely feedback will be provided to weekly progress.
The MEP student will also be embedded in the larger research team meetings, both as contributor and observer.
Timely feedback will be provided to weekly progress.