Handheld Log Scanner Fusing Depth and Texture Images
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Solution Overview
Problem
The forestry industry faces inefficiencies in log identification, measurement, and counting due to labor-intensive manual processes and limitations of existing automated systems, which hinder the supply chain and are costly.
Innovation Solution
A handheld scanner system that uses depth and texture sensors to capture images of log ends, fusing data to create models, decode ID elements, and generate output data for log count, measurement, and association, allowing for efficient log identification and measurement in situ on logging trucks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual log scaling is performed by log scalers, then log identification and measurement can be conducted, but labor costs are high and processing efficiency is low
Solution Approach 1:
The patent replaces manual mechanical log scaling with an automated optical scanning system using depth sensors and texture sensors. The handheld scanner captures images of log ends, and image processing algorithms automatically identify log boundaries, decode ID elements, and extract measurement data, eliminating the need for manual log scalers and significantly improving processing efficiency
Solution Approach 2:
The patent creates digital copies of log end faces through depth images and texture images. These image copies are then processed to extract log measurements and ID information, replacing the need for physical manual measurement while preserving all necessary data for log identification and scaling
2Productivity
If automated log measuring systems are deployed, then labor costs are reduced, but system complexity and cost increase
Solution Approach 1:
The handheld scanner is designed as a multi-functional device that combines depth sensing, texture sensing, and handheld portability into a single unit. This universal device can perform multiple functions including log boundary detection, ID element decoding, and measurement extraction, reducing the need for multiple specialized systems while maintaining automated processing capability
Solution Approach 2:
The patent introduces image processing algorithms as an intermediary between the physical log and the measurement data. The depth and texture images serve as intermediate representations that bridge the physical log characteristics and the extracted measurement information, simplifying the overall system architecture by using software processing rather than complex mechanical measurement mechanisms
3Adaptability or versatility
If existing automated systems are used, then some automation is achieved, but they cannot scan logs in situ on logging trucks
Solution Approach 1:
The patent employs a handheld scanner that can be dynamically moved and positioned by an operator to scan log ends in various locations, including on logging trucks. The system adapts to different scanning positions and orientations, providing operational flexibility while maintaining automated processing capability that fixed systems cannot achieve
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system significantly reduces labor costs and increases efficiency by enabling rapid and accurate log identification and measurement, improving the supply chain process and reducing bottlenecks in log export and domestic supply.
Implementation Method 1
sensors for depth sensing and texture sensing, the sensors configured to capture: a series of depth images of the load end face
Implementation Method 2
sensors for depth sensing and texture sensing, the sensors configured to capture: a series of texture images of the load end face
Implementation Method 3
a data processor or processors that receives the series of depth images and texture images captured from the scan, and which are configured to: fuse the depth images into a data model of the load end face
Data Source
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AI summary
A log scanning system and method for scanning a log load. Each individual log in the log load may have an ID element with a unique log ID data on at least one log end face. The system has a handheld scanner unit for free-form scanning by an operator over a load end face of the log load. The scanner unit has a depth sensor configured to capture a series of depth images of the load end face and a texture sensor configured to capture a series of texture images of the load end face during the load end face scan. The system also has a data processor(s) that receives and processes the depth and texture images captured from the scan. The processor(s) are configured to fuse the depth images or depth and texture images into a data model of the load end face, determine log end boundaries of the individual logs visible in the load end face by processing the data model, process the texture images to identify and decode any ID elements visible in the scan to extract individual log ID data, and generate output data representing the log load based on the determined log end boundaries and extracted log ID data.