The United States of America As Represented by the Secretary of

Virginia Tech Intellectual Properties, Inc.

Virginia Polytechnic and State University

Richard W Conners

Phillip A Araman

David E Kline

Thomas H Drayer

Qiang Lu

Xiangyu Xiao

A machine vision system that can address a number of board, lineal, cant, and flitch inspection problems by incorporating all the sensors needed to address the surface feature detection problem, the three-dimensional shape detection problem, and the internal feature detection problem. To detect surface features, two color cameras are employed, one for imaging each of the major faces of a board, lineal, cant, or fitch. To address the three-dimensional shape detection problem, a high speed laser profiling device is employed. An x-ray scanning system is employed to detect internal features. The system is able to process material in a species-independent manner by using a histogram-based segmentation procedure for analyzing both the camera imagery and the x-ray imagery; and can detect small defects by removing the effects of large features from the histograms once they have been detected. The system also utilizes redundant information from the set of multiple sensors to improve system accuracy. The volume of data that must be analyzed due the use of three sets of sensors is reduced by ordering the way the data is analyzed. The laser profile data is processed first, followed by the x-ray data and the color imagery. Finally, the system reduces the required volume of data by incorporating a crack/check preserving filter. This filter is implemented in special purpose hardware, and filters the color imagery as it is collected.

Defect detection system for lumber

A system for automatically color and grain sorting materials includes a pair of color cameras positioned to view the top and bottom faces, respectively, of each part. A computer analyzes the data from the top and bottom cameras, and also controls the voltage on the input line to each camera. Camera controllers accept analog data from the camera heads and digitize it so that the information can be passed to the computer for analysis. A white target inserted into the field of view of each camera allows the computer to collect the data needed to do 'shading compensation' on the collected color image data. Three basic categories of algorithms are used in the sorting system in accordance with the present invention: (1) training algorithms used to teach the system to identify the color and grain classes that are to be used during the sorting process, (2) real-time operation algorithms which perform the color and grain sorts with parts moving through the system at the desired throughput rate, and (3) utility algorithms which allow operators to display images, perform system tests, etc. In the training and sorting algorithms, the computer produces a black/white histogram of a part face based on the data analysis, and applies a character mark algorithm to the black/white histogram to find a threshold value for eliminating the effects of character marks from the color and grain classification and sorting of the part.

Automatic color and grain sorting of materials

Growing community of inventors

Blacksburg, VA, United States of America

Richard W Conners