Rapid and Robust Automated Macroscopic Wood Identification System using Smartphone with Macro-lens

TL;DR

This paper presents a fast, cost-effective smartphone-based system for macroscopic wood identification that achieves human-level accuracy, aiding law enforcement in illegal timber detection.

Contribution

It introduces a novel, scalable machine vision system using smartphones and macro-lenses for rapid, accurate wood identification in the field.

Findings

System provides identification within seconds.

Achieves accuracy comparable to expert anatomists.

Cost-effective and accessible for field use.

Abstract

Wood Identification has never been more important to serve the purpose of global forest species protection and timber regulation. Macroscopic level wood identification practiced by wood anatomists can identify wood up to genus level. This is sufficient to serve as a frontline identification to fight against illegal wood logging and timber trade for law enforcement authority. However, frontline enforcement official may lack of the accuracy and confidence of a well trained wood anatomist. Hence, computer assisted method such as machine vision methods are developed to do rapid field identification for law enforcement official. In this paper, we proposed a rapid and robust macroscopic wood identification system using machine vision method with off-the-shelf smartphone and retrofitted macro-lens. Our system is cost effective, easily accessible, fast and scalable at the same time provides human-level accuracy on identification. Camera-enabled smartphone with Internet connectivity coupled with a macro-lens provides a simple and effective digital acquisition of macroscopic wood images which are essential for macroscopic wood identification. The images are immediately streamed to a cloud server via Internet connection for identification which are done within seconds.