Research to develop an annotated bark image bank of hardwood trees in the Central Hardwood region, as well as an AI algorithm for bark-based species recognition and a smartphone app for bark-based tree species identification.

student working on cross-section of tree trunk

Principal Investigators

Rado Gazo | Professor of Wood Processing and Industrial Engineering
Bedrich Benes | George W. McNelly Professor of Technology and Professor of Computer Science

Collaborators

Songlin Fei | Professor and Dean’s Chair of Remote Sensing

OBJECTIVES

The main goal of this project is to develop smartphone app to correctly identified tree species by their bark for hardwood trees in the Central Hardwood region.

Specific objectives are:

  • Develop a standard protocol for data collection.
  • Develop a smartphone app that will allow users to acquire images of tree bark and associated data in the field, and transmit this data to a central database.
  • Develop a central database that will house the collected information, allow for verification and data labeling, query, and sharing among researchers.
  • Develop Bark ID app
  • Organize workshops to train professionals and the public on using the bark ID app. Additionally, organize an international workshop for researchers working on AI approaches to tree bark identification.