Mitutoyo Corporation

Richard M Wasserman

Paul Gerard Gladnick

Dahai Yu

Kim W Atherton

Ana M Tessadro

Andrew David Silber

Systems and methods are provided for excluding extraneous image features from inspection operations in a machine vision inspection system. The method identifies extraneous features that are close to image features to be inspected. No image modifications are performed on the 'non-excluded' image features to be inspected. A video tool region of interest provided by a user interface of the vision system can encompass both the feature to be inspected and the extraneous features, making the video tool easy to use. The extraneous feature excluding operations are concentrated in the region of interest. The user interface for the video tool may operate similarly whether there are extraneous features in the region of interest, or not. The invention is of particular use when inspecting flat panel display screen masks having occluded features that are to be inspected.

System and method for excluding extraneous features from inspection operations performed by a machine vision inspection system

An illumination technique is provided that adjusts the respective light intensities of each of a plurality of light sources that are strobed at desirable consistent intensities by adjusting a respective light pulse pattern for each respective light source. All the light sources are controlled to illuminate an object throughout a strobe duration period. The light pulse patterns may be micro-strobed light pulse patterns, formed by a variety of methods. The illumination technique is usable to preserve the general shape of the edge intensity profile on an object, and allow precision edge position measurements, regardless of whether the object is moving or not during image acquisition.

Strobe illumination

A method and apparatus for tracing an edge contour of an object in three dimensional space is provided. The method and apparatus is utilized in a computer vision system that is designed to obtain precise dimensional measurements of a scanned object. In order to save focusing time during an automatic tracing measurement, multiple images may be collected and saved for a number of Z heights for a particular position of the XY stage. These saved images can later be used to calculate a focal position for each edge point trial location in the selected XY area rather than requiring a physical Z stage movement. In addition, a Z height extrapolation based on the Z heights of previous edge points can significantly speed up the searching process, particularly for objects where the Z height change of a contour is gradual and predictable.

Method and apparatus for three dimensional edge tracing with Z height adjustment

The systems and methods of this invention provide simulated images to vision inspection systems. The simulated images emulate the vision of a vision inspection system. Graphical models of objects in a virtual world and lens effects models are used to provide the simulated images.

Hardware simulation systems and methods for vision inspection systems

Auto focus systems and methods for a machine vision metrology and inspection system provide high speed and high precision auto focusing, while using relatively low-cost and flexible hardware. One aspect of various embodiments of the invention is that the portion of an image frame that is output by a camera is minimized for auto focus images, based on a reduced readout pixel set determined in conjunction with a desired region of interest. The reduced readout pixel set allows a maximized image acquisition rate, which in turn allows faster motion between auto focus image acquisition positions to achieve a desired auto focus precision at a corresponding auto focus execution speed that is approximately optimized in relation to a particular region of interest. In various embodiments, strobe illumination is used to further improve auto focus speed and accuracy. A method is provided for adapting and programming the various associated auto focus control parameters.

Systems and methods for rapidly automatically focusing a machine vision inspection system

Systems and methods where a lighting configuration of a vision system is determined using a controllable lighting system and at least one image evaluation tool. The lighting configuration is usable to obtain a desired inspection image of at least one feature of a workpiece Base images are obtained using actual illumination settings of the controllable lighting system. Simulated or synthetic sets image results are generated, based on base images and synthetic lighting configurations. The synthetic lighting configurations include at least one illumination setting which is different from the actual illumination settings used to obtain one or more component base images. A best actual or synthetic lighting configuration is chosen based on the best corresponding set of image results.

System and methods for determining the settings of multiple light sources in a vision system

The defocused image generating methods and systems defocus an image using sets of image elements of a multi-resolution pyramid representation of the input image. Each pixel in the original image generates a region of confusion based on the image depth data for that pixel. The sets of image elements are used to represent the region of confusion using increasingly higher resolution image elements. The final defocused image is generated by compositing or combining together the sets of image elements after the region of confusion of each pixel has been decomposed into the sets of image elements.

Systems and methods for multi-resolution image defocusing

Image simulation system and method simulate an image based on a number of base images and a current lighting vector. An actual object to be viewed using the vision system is placed within the overall field of view of the vision system. Depending on the desired analysis to be made, either the entire object, or a specific portion of the object, is illuminated using one of the various illumination sources of the vision system. The base images of the objects, or of the particular portion of the object, are captured, where each base image is illuminated using a different illumination intensity of that single illumination source. This is repeated for each of the different illumination sources provided in the vision system. The simulated image is generated by combining various ones of the base images based on the light intensities of the lighting services defined in the current lighting vector. The simulated image can be evaluated to determine if it has a desired image quality. The lighting vector can be modified until a simulated image having the desired image quality is obtained. That lighting vector can then be used to obtain an actual image of the object that will have the desired image quality.

System and methods to determine the settings of multiple light sources in a vision system

The lighting behavior of a vision system is inconsistent between vision systems, within a vision system over time or between parts being viewed. This inconsistency makes it difficult to correctly run part programs even within a single run of parts on a single machine. The multi area image quality tool systems, methods and graphical user interfaces adjust the light intensity of a vision system to obtain a desired image quality or characteristic of a captured image. The multi area image quality tool is used to define a plurality of regions of interest within a captured image to be used to determine the image quality or characteristic of the captured image resulting from a current illumination level. The multi area image quality tool allows a user to easily and quickly define multiple regions of interest that can be used to determine the image quality of a captured image. The multi area image quality tool allows the user to specify the location, orientation and size of two or more regions of interest around a critical feature of the captured image, and to specify the light sources to be used to illuminate the part, the image quality to be measured, and a range of acceptable values for that image quality. Portions of the image are extracted based on the defined regions of interest. The image quality of the captured image is determined based on an analysis of the regions of interest and the image quality defined in the multi area image quality tool.

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Redmond, WA, United States of America

Richard M Wasserman