Invention Grant
- Patent Title: Method and system for ensuring the quality of a wood product based on surface irregularities using near infrared imaging and machine learning
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Application No.: US16697461Application Date: 2019-11-27
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Publication No.: US10933556B2Publication Date: 2021-03-02
- Inventor: David Bolton , Jude Richard Peek , Curtis Fennell
- Applicant: Boise Cascade Company
- Applicant Address: US ID Boise
- Assignee: Boise Cascade Company
- Current Assignee: Boise Cascade Company
- Current Assignee Address: US ID Boise
- Agency: Hawley Troxell Ennis & Hawley LLP
- Agent Philip McKay
- Main IPC: G01J5/00
- IPC: G01J5/00 ; B27K5/00 ; H04N5/33 ; G01N21/359 ; G06N7/02 ; G06T1/20 ; G01N21/3563

Abstract:
Near InfraRed NIR technology, including NIR cameras and detectors, and machine learning methods and systems, including one or more Machine Learning (ML) based surface irregularity prediction models, are used to accurately identify surface irregularities on a surface of a wood product, such as a veneer sheet or ribbon, and provide irregularity prediction data for the wood product. Based on the irregularity prediction data for a given wood product, one or more actions are taken with respect to wood product or the production process to ensure the wood product is put to the most efficient, effective, and valuable use.
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