Applied Vision Corporation

Applied Vision Company, LLC

Michael Leo Kress

Richard A Sones

Carl E Sebeny

Brian M Baird

Michael A Kress

Kris Brumbaugh

Amir R Novini

Kellen Reusser

Bryan Murdoch

Benjamin James Crissman

Jacob Joseph Trombetta

Brian M Ensinger

A container inspection system is described herein. The container inspection system includes a camera and a computing system, wherein the camera is configured to capture multiple images of a transparent container as the transparent container is transported along a conveyor. Thus, the camera captures several images of the transparent container when the transparent container is at different positions relative to the camera. The container inspection system detects a defect in the transparent container based upon one or more images in the several images.

Sequential imaging for container sidewall inspection

A glass container inspection system including a diffuse illuminator configured to provide diffused light arranged to illuminate a portion of a glass container symmetrically about a central axis of the container. The inspection system further includes an image capture system that generates at least one image that includes a plurality of views of the glass container illuminated by the diffused light. The at least one image may include a view of the portion of the container reflected by a mirror. The glass container inspection system yet further includes a computing system in communication with the image capture system. The computing system can be configured to output an indication as to whether the container is defective based upon the data from the image capture system. The computing system can be further configured to output the indication responsive to detecting a check in the sidewall of the glass container.

Glass container inspection system

Described herein are various technologies pertaining to an automated light field illumination container inspection and manufacture system. The system includes a plurality of cameras that capture images of a container when the container is illuminated by way of light field illumination. Bands in images that include reflections in the exterior surface of the sidewall are identified, and a determination is made as to whether the container is defective based upon the identified bands.

Container inspection system controlling printheads to correct for detected ink thickness errors

Described herein are various technologies pertaining to determining whether at least a portion of a sidewall of a glass container has insufficient thickness. A glass container inspection system comprises an infrared camera in communication with a computing system. The infrared camera is configured to capture an infrared image of an exterior of the sidewall of the glass container at long-wavelength infrared as the glass container undergoes a temperature change. The computing system receives the infrared image from the infrared camera and outputs an indication that at least the portion of the sidewall of the glass container has insufficient thickness based on the infrared image. The indication may also be based on a statistical model derived from infrared images of glass containers having sidewalls of known sufficient thickness.

Described herein are various technologies related to inspecting transparent containers for both opaque and transparent defects. An emitter is configured to direct a color gradient through a sidewall of a transparent container, such that color of light that passes through the sidewall varies across the sidewall. A camera is configured to capture an image of the sidewall of the transparent container while the color gradient passes through the sidewall of the container. A computing system receives the image and determines whether the sidewall of the container includes either an opaque or a transparent defect based upon the image.

Identifying defects in transparent containers

A container inspection system is described herein. The container inspection system includes a light source that emits a flash of light when a container is detected as being in an inspection region. The container inspection system further includes a light director element that receives a portion of the flash of light and forms a tapering field of light that illuminates an exterior surface of a sidewall of the container when the container is in the inspection region. The container inspection system further comprises a camera that generates an image of the exterior surface when such surface is illuminated by the tapering field of light. A computing system receives the image and outputs an indication as to whether or not the container is defective based upon the image.

Container inspection system

Described herein are various technologies pertaining to an automated light field illumination container inspection. The container inspection system includes a plurality of cameras that capture images of a container when the container is illuminated by way of light field illumination. Bands in images that include reflections in the exterior surface of the sidewall are identified, and a determination is made as to whether the container is defective based upon the identified bands.

Light field illumination container inspection system

Systems and methods for extracting topographic information from inspected objects to identify defects in the inspected objects. A part to be inspected is illuminated with at least two different colors emitted from an illuminator providing a gradient of light consisting of the at least two different colors. A single color image of the illuminated part to be inspected is acquired, providing a color-coded topographic mapping of the part to be inspected due, at least in part, to the gradient of light. Topographic monochrome views of the part to be inspected may be generated from the single color image. Each view of the topographic monochrome views may enhance a different type of feature or defect present in the part to be inspected which can be analyzed and detected.

Apparatus and methods for extracting topographic information from inspected objects

A method and configuration to estimate the dimensions of a cuboid. The configuration includes two image acquisition units offset from each other with at least one of the units positioned at a defined acquisition height above a background surface. Image processing techniques are used to extract a perimeter of a top surface of the cuboid, placed on the background surface, from pairs of acquired images. A height estimation technique is used to calculate an absolute height of the cuboid. The absolute height of the cuboid is used, along with the extracted perimeter of the top surface of the cuboid, to calculate an absolute length and an absolute width of the cuboid. The height, length, and width may be used to calculate an estimated volume of the cuboid.

System and method for dimensioning objects using stereoscopic imaging

Apparatus, systems, and methods to recognize features on bottom surfaces of containers on a container production line, detect defects in the containers, and correlate the defects to specific production equipment of the container production line, based in part on the recognized features. The system includes imaging apparatus, programmable processing devices, and encoders. The methods include synchronization techniques and correlation techniques.

Apparatus and methods for container inspection

Apparatus, systems, and methods to recognize features on bottom surfaces of containers on a container production line, detect defects in the containers, and correlate the defects to specific production equipment of the container production line, based in part on the recognized features. The system includes imaging apparatus, programmable processing devices, and controllers. The methods include imaging techniques and estimation techniques.

Apparatus, systems, and methods to recognize features on bottom surfaces of metal containers on a metal container production line, detect defects in the metal containers, and correlate the defects to specific production equipment of the metal container production line, based in part on the recognized features. The system includes imaging apparatus, programmable processing devices, and controllers. The methods include imaging techniques and estimation techniques.

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Uniontown, OH, United States of America

Michael Leo Kress