Lucidyne Technologies, Inc.

Other

Patrick S Freeman

George M Carman

William J Briskey

Ofer Heyman

Joseph H Weintraub

Hayden Michael Aronson

Ryan T Shear

Eric N Mortensen

Chris Mosbrucker

Dan Robin

Revathy Priyanga Narasimhan

Kevin Johnsrude

Paul Shirkey

Aaron R Paul

David D Ayers

David K Christopher

Chad D Gibson

A method of board lumber grading is performed in an industrial environment on a machine learning framework configured as an interface to a machine learning-based deep convolutional network that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method uses deep learning techniques that are applied to semantic segmentation to delineate board lumber characteristics, including their sizes and boundaries.

Board lumber grading using deep learning semantic segmentation techniques

Method of board lumber grading using deep learning techniques

A frameless portable water panel for displaying advertising and products constructed of transparent material combining a water wall column and cascading water tanks supporting dry, removable display shelves. Water is pumped into a tall water column from a bottom reservoir with a water pump. Water fills the tall water column and flows down on the outside of the front wall of the column then into a series of cascading water tanks before returning to the bottom reservoir. An alternate embodiment is modified to serve as a self-serve drinking fountain by removing the lowest shelf and adding fountain openings in the outside face of the front wall of one of the cascading tanks. Other modifications including bevel top edges on the water column, a light pan under the unit, pegs to secure the shelves, clear splash guards on the back of all shelves, and supporting legs under each shelf.

Water panel

A grain angle sensor system for measuring grain angle direction of surface fibers of a wood object with respect to at least one of a surface plane direction or a transverse direction, such as a dive angle, or with respect to both the surface plane and transverse direction. The system includes multiple laser diodes and photosensor detectors integrated into an electro-optical assembly that can sequence the firing of the lasers to minimize crosstalk. An exemplary assembly includes an enclosure housing an electronic control board connected to circuit cards containing multiple laser diodes and multiple photosensor detectors.

Grain angle sensor

A 'Woodprint&#x2122;' characterization and identification technique employs cameras (), lighting (), camera interface hardware (), a computer (), and/or image processing software to collect and analyze surface characteristics of pieces of wood () to track them through an automated production process in real-time with information that is specific to each wood piece (), such as what machining is required, its value, and/or its destination. When a wood piece () reaches a point in the production process where a decision is required, its unique identity is used to retrieve appropriate information previously determined and assigned to the wood piece ().

Wood tracking by identification of surface characteristics

A 'woodprint&#x2122;' characterization and identification technique unique employs cameras (), lighting (), camera interface hardware (), a computer (), and/or image processing software to collect and analyze surface characteristics of pieces of wood () to track them through an automated production process in real-time with information that is specific to each wood piece (), such as what machining is required, its value, and/or its destination. When a wood piece () reaches a point in the production process where a decision is required, its unique identity is used to retrieve appropriate information previously determined and assigned to the wood piece ().

The present invention employs a blinded fiber-optic light illumination system ( ) to illuminate a wood board ( ) with a sharp projected light edge to detect the tracheid, color, and geometric characteristics of the lumber during an automated grading process. The light line ( ) employs thousands of fibers ( ) of desired length ( ) and thickness ( ). The fibers ( ) are randomized such that fibers ( ) neighboring each other in the cable ( ) do not necessarily neighbor each other in the light line subunit ( ) so that the emitted light has substantially uniform intensity over its spatial range. Multiple light line subunits ( ) are positioned adjacent to one an other to achieve a desired light line length ( ). A set of image sensors ( ) in predetermined positions obtain three types of data from the light incident to the board ( ). A computer analyzes the data to interpret the physical characteristics of the board ( ) and determine how to grade or cut it.

Fiber-optic light line for use in an inspection system

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Brownsville, OR, United States of America

Patrick S Freeman