Log evaluation using cylindrical projections

X-ray or gamma ray systems or devices – Specific application – Absorption

Reexamination Certificate

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C378S004000, C382S154000, C702S035000, C702S040000

Reexamination Certificate

active

06597761

ABSTRACT:

COPYRIGHT NOTICE
A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever.
REFERENCE TO APPENDIX ON COMPACT DISC
An Appendix containing a computer program listing is submitted on a compact disc, which is incorporated by reference herein in its entirety. The total number of compact discs including duplicates is two. Each of the compact discs includes a file named “RadiallmageCode.txt”, which was created Jan. 26, 2001 and has a size of 44,826 bytes.
BACKGROUND
Logs are non-standard commodities that contain defects such as knots and cracks that significantly affect the value of boards cut from the log. Accordingly, when buying logs, a grader evaluates each log to determine the extent and locations of defects in the log. A sawyer, when cutting the log, attempts to select a sawing strategy that provides the highest value for the lumber cut from the log. These graders and sawyers typically depend on the external appearance of a log when grading or evaluating the log, but viewing the exterior of a log gives the grader or sawyer an imprecise indication of the quality of a log and often fails to indicate internal defects. This results in economic inefficiency because logs are inaccurately graded or cut.
Log scanning devices have been developed to improve the evaluation of logs and the optimization of sawing strategies. For example, U.S. Pat. No. 5,394,342 describes a scanning system that applies circumferentially spaced traverse scans along the length of a log to provide longitudinal density data. A paper by D. Schmoldt, entitled “CT Imaging, Data Reduction, and Visualization of Hardwood Logs,” Hardwood Symposium Proceedings, (May 1996) and a paper D. Schmoldt et al entitled “Nondestructive Evaluation of Hardwood Logs: CT Scanning, Machine Vision and Data Utilization,” Nondestr. Test Eval., Vol. 15 (1999) describe CT (computer tomography) scanning of logs and evaluation of data resulting from CT scanning of a log.
The three-dimensional data structures and the large amount of data that scanners generate for a log are often difficult to use. For example, data indicating a three-dimensional density distribution for a log is difficult for a grader or sawyer to visualize, and computer manipulation of the large amount of data requires significant processing power or time. Efforts are continuing to improve the methods for quantifying the properties of logs, visualizing the data associated with the logs, and optimizing log grading and sawing strategies based on such data.
SUMMARY
In accordance with an aspect of the invention, a three-dimensional density distribution for a log is processed to provide a convenient image or visualization of defects like knots or voids in a log and thereby facilitate grading and optimization of a sawing strategy for a log. The data representing such images has a two-dimensional structure and contains considerably less data than a three-dimensional density distribution. Accordingly, manipulation of data structures in accordance with the invention requires less processing power or time in automated processes for grading or optimization of a sawing strategy. Other aspects of the invention provide processes for grading and optimizing the sawing strategies based on the two-dimensional data structures.
In one embodiment, a visualization of a log provides a two-dimensional image where intensities (or colors) in the image correspond to a property evaluated along at least portions of cylindrical projections extending from the center of the log. Exemplary properties shown in the image include but are not limited to the average density along a projection, a minimum or maximum density along a projection, existence of a steep change in density along a projection, and flags indicating the presence or absence of defects along a projection. A central axis from which the projections extend can be straight or can follow the center of growth rings in the log, and the projections can be perpendicular to the axis or extend at an upward angle characteristic of the branches in a tree. A viewer of this image can quickly identify an orientation for the log that presents the fewest defects to a first cut of a saw blade.
One exemplary embodiment of the invention is a data structure for describing a log. The data structure includes a two-dimensional array of data values. Each data value corresponds to values of a coordinate Z and a second coordinate &thgr;. The coordinate Z indicates distance along the log, and the coordinate &thgr; indicates an angle around the log. Each data value indicates a property of the log that is evaluated along a ray that originates at a center point corresponding to the value of the coordinate value Z and extends in a direction corresponding to the coordinate value &thgr;. The center point at each value of the coordinate Z is typically the growth center of the log at that Z-coordinate value but alternatively can be the geometric center of the log or of core wood in the log. The ray evaluated to determine a data value can be perpendicular to the length of the log or directed at an upward angle along the log. The upward angle typically depends on a growth direction characteristic of tree limbs in the species of tree that produced the log or is determined independently for each log. Optionally, each data value indicates a property of the log that is evaluated in a range of distances along the ray that originates at the center point. The range can be limited to exclude core wood in the center of log and or bark on the outside of the log. In one specific embodiment, each data value indicates presence or absence of a defect corresponding to the coordinates of the data value and may further indicate the depth or location along the ray for any defect on the ray.
Another embodiment of the invention is a method for generating a description of a log. For a set of locations along the length of the log, the method finds a center point (e.g., a geometric or growth center) of the log. Each ray in a set of rays that extend from the center points is evaluated. In particular, the method evaluates a property of the log along each ray to generate a data value corresponding to Z and &thgr; coordinates identifying the direction of the ray. Typically, the evaluated property is density along the ray, and the evaluation determines whether there is a defect along the ray. A CT scan of the log can generate a three-dimensional data structure that provides the densities evaluated along the rays. A two-dimensional data structure that describes the log includes the data values, which are positioned in the two-dimensional data structure according to their respective coordinates.
Another embodiment of the invention is a system for evaluating logs. The system includes program code that is computer executable for manipulating a data structure such as described in the preceding paragraph. Generally, the system further includes a display device and a processor capable of executing the program code. In executing the program code, the processor controls display of an image on the display device. The image includes pixels that correspond to the data values of the data structure and have shades defined by the respective data values. The system can further superimpose marks on the image to indicate boundaries of one or more faces of the log that results from sawing the log. The marks can be shifted relative to the image identify an optimal orientation for sawing the log that minimizes the defects present between the boundary marks, i.e., in the cut faces of the log.
Another embodiment of the invention is method for grading a log. The grading method uses a two-dimensional defect structure or data array as described above that includes data values indexed by cylindrical or modified cylindrical coordina

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