AI Vision System for Real-Time Wood Defect Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The wood industry faces significant raw material losses due to inefficiencies in manual processing, with existing automation solutions failing to provide precise classification and quality grading, especially for small and medium-sized companies, and existing systems are limited by debris accumulation and inflexibility in installation on various production lines.
Innovation Solution
A system utilizing advanced algorithms of artificial intelligence and computational vision with industrial cameras and sensors, capable of detecting defects and calculating optimal cuts in real-time, which can be easily installed on any production line with customizable sensor placement, reducing material losses and improving productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cameras are positioned above and below the conveyor to capture all board surfaces, then classification completeness is improved, but debris accumulates on lower cameras reducing reliability
Solution Approach 1:
The patent transitions from a 2D camera arrangement (above and below conveyor) to a 3D spatial configuration by positioning cameras at angled positions on the side of the conveyor. This dimensional change allows cameras to capture board surfaces without being directly exposed to debris accumulation zones, maintaining classification completeness while improving operational reliability.
Solution Approach 2:
The patent introduces an intermediary optical system comprising mirrors and additional cameras positioned at angles. This intermediary configuration allows indirect capture of board surfaces that would otherwise require direct line-of-sight from cameras positioned in debris-prone areas, thereby maintaining measurement precision while protecting camera reliability.
2Measurement precision
If a fixed camera positioning system with precise angular tolerance is used, then measurement accuracy is improved, but adaptability to different production lines is reduced
Solution Approach 1:
The patent employs adjustable and reconfigurable camera positioning mechanisms that allow the system to adapt to different production line configurations. The cameras can be dynamically positioned at various angles and locations while maintaining measurement accuracy through real-time calibration and optical adjustment, thereby achieving both precision and adaptability.
Solution Approach 2:
The patent designs a universal camera system with standardized mounting interfaces and configurable optical paths that can be adapted to multiple production line types. The system maintains measurement precision across different applications through programmable positioning and calibration routines, enabling versatile installation while preserving accuracy.
3Measurement precision
If multiple cameras are positioned at precise angles to capture all board faces, then classification accuracy is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple camera views and optical paths into a unified image processing pipeline. By merging the captured images from various angles and using integrated processing algorithms, the system achieves high classification accuracy while managing complexity through consolidation of data streams and centralized control.
Solution Approach 2:
The patent uses virtual copying techniques where digital models and synthetic images are generated to supplement physical camera captures. This allows the system to achieve comprehensive board surface analysis without requiring physically complex multi-camera arrangements, reducing hardware complexity while maintaining classification accuracy.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
This invention pertains to a system for detecting defects in wooden boards and classifying them into quality classes, which uses advanced algorithms of artificial intelligence and computational vision used for grading/classifying wooden boards. The system according to the invention proposes a solution for the automated grading of wooden boards, particularly lumber, using last generation industrial cameras in order to acquire color images (RGB) of the faces of the boards, images which, further, are processed and analyzed by advanced algorithms of artificial intelligence and computational vision. The system enables the detection of various types of wood defects with high precision, calculates in real time the optimal cuts and the quality class to which the board belongs, on the production line, being a solution adequate also for small and medium-sized companies, thanks to the low cost of implementation and operation.