Edge location measurement correction for coaxial light images

A method for correcting coaxial light image edge location errors in a precision machine vision inspection system is disclosed. The method comprises comparing an edge position measurement of a workpiece edge feature using coaxial light and stage light. Edge position measurements using stage light have a lower uncertainty than that of coaxial light. Position correction factors may be determined from the difference between the two edge position measurements. The position correction factors may be stored for correcting subsequent edge position measurements that are based on images acquired using coaxial light. In some embodiments, position correction factors may be determined based on comparing edge position measurements for a plurality of edges.

FIELD OF THE INVENTION

The invention relates generally to machine vision inspection systems, and more particularly to methods of correcting illumination-dependent errors in edge location measurements.

BACKGROUND

Precision machine vision inspection systems (or “vision systems” for short) can be utilized to obtain precise dimensional measurements of inspected objects and to inspect various other object characteristics. Such systems may include a computer, a camera and optical system, and a precision stage that is movable in multiple directions so as to allow the camera to scan the features of a workpiece that is being inspected. One exemplary prior art system that is commercially available is the QUICK VISION® series of PC-based vision systems and QVPAK® software available from Mitutoyo America Corporation (MAC), located in Aurora, Ill. The features and operation of the QUICK VISION® series of vision systems and the QVPAK® software are generally described, for example, in theQVPAK3D CNC Vision Measuring Machine User's Guide, published January 2003, and theQVPAK3D CNC Vision Measuring Machine Operation Guide, published September 1996, each of which is hereby incorporated by reference in their entirety. This product, as exemplified by the QV-302 Pro model, for example, is able to use a microscope-type optical system to provide images of a workpiece at various magnifications, and move the stage as necessary to traverse the workpiece surface beyond the limits of any single video image. A single video image typically encompasses only a portion of the workpiece being observed or inspected, given the desired magnification, measurement resolution, and physical size limitations of such systems.

Machine vision inspection systems generally utilize automated video inspection. U.S. Pat. No. 6,542,180 (the '180 patent) teaches various aspects of such automated video inspection and is incorporated herein by reference in its entirety. As taught in the '180 patent, automated video inspection metrology instruments generally have a programming capability that allows an automatic inspection event sequence to be defined by the user for each particular workpiece configuration. This can be implemented by text-based programming, for example, or through a recording mode which progressively “learns” the inspection event sequence by storing a sequence of machine control instructions corresponding to a sequence of inspection operations performed by a user with the aid of a graphical user interface, or through a combination of both methods. Such a recording mode is often referred to as “learn mode” or “training mode.” Once the inspection event sequence is defined in “learn mode,” such a sequence can then be used to automatically acquire (and additionally analyze or inspect) images of a workpiece during “run mode.”

The machine control instructions including the specific inspection event sequence (i.e., how to acquire each image and how to analyze/inspect each acquired image) are generally stored as a “part program” or “workpiece program” that is specific to the particular workpiece configuration. For example, a part program defines how to acquire each image, such as how to position the camera relative to the workpiece, at what lighting level, at what magnification level, etc. Further, the part program defines how to analyze/inspect an acquired image, for example, by using one or more video tools such as edge/boundary detection video tools.

Video tools (or “tools” for short) and other graphical user interface features may be used manually to accomplish manual inspection and/or machine control operations (in “manual mode”). Their set-up parameters and operation can also be recorded during learn mode, in order to create automatic inspection programs, or “part programs.” Video tools may include, for example, edge/boundary detection tools, autofocus tools, shape or pattern-matching tools, dimension-measuring tools, and the like.

Machine vision inspection systems may illuminate a workpiece edge feature using various types of illumination. For example, stage light and coaxial light are discussed in the '180 patent. High resolution edge location measurements may return different results depending on the type of illumination used when acquiring an image that is used for edge location. Various methods are known in the art for correcting the different results of edge location measurements obtained using different types of illumination. For example, a publication by Fu et al. (Thickness Correction for Edge Detection of Optical Coordinate Measuring Machines, ASPE Proceedings, Oct. 31-Nov. 5, 1999, Monterey Calif.) describes various methods for compensating for errors associated with such measurements. However, the methods employed therein are impractical for a number of applications. For example, they are time consuming, may require a special reference object to measure, and may be too complex for implementation by a relatively unsophisticated user of a machine vision inspection system. Additionally the methods address errors which arise from thickness of an edge feature and do not provide adequate high accuracy compensation/correction directed to the variety of edge conditions and workpiece materials encountered by a general purpose machine vision inspection system. Improvements in methods for correcting edge location results such that they are consistent and accurate, regardless of the type of illumination used for image acquisition, would be desirable.

SUMMARY

A method is provided for correcting edge location results such that they are consistent and accurate for types of illumination that may otherwise cause a shift in an imaged edge position (e.g., an offset or bias) when used to illuminate an image of the edge. In particular, it has been found that certain machine vision inspection systems may be designed such that its stage light provides relatively ideal (e.g., consistent and accurate) imaged edge positions. However, in contrast, it has been found that coaxial light provides an offset or bias in imaged edge positions. Therefore, briefly stated, in various embodiments, a method according to this invention establishes a reference measurement of an edge based on a “stage light image”; establishes a “coaxial light measurement” of the same edge in a “coaxial light image”; determines a difference between the coaxial light measurement and the stage light reference measurement; and corrects subsequent edge location measurements in coaxial light images based on that difference. Such a method has been found to be both simpler and more accurate in certain vision systems than previously known methods of correcting illumination-dependent edge location errors. In addition, the method may be implemented without the need for a precisely fabricated reference object. In some embodiments, such a method may be implemented as a generic illumination-dependent correction for the machine vision inspection system. In some embodiments, such a method may be implemented for a specific workpiece type or a specific workpiece edge, based on learn mode operations that use a representative workpiece to establish a workpiece-specific or edge-specific illumination-dependent correction applicable to coaxial light measurements on subsequent similar workpieces and/or edges.

In various embodiments, the machine vision inspection system comprises an imaging system, a workpiece stage, a coaxial illumination portion which projects coaxial light from an objective lens of the imaging system toward the workpiece stage, a stage light illumination portion which projects stage light from the workpiece stage toward the imaging system, and a control system. In some embodiments, the stage light comprises a light generator and collimating optics that output collimated stage source light. In some embodiments, the stage light also comprises an output light diffuser that inputs collimated light and outputs stage source light that is at least partially diffuse. The method comprises the steps of: (a) positioning a workpiece on the workpiece stage with an edge feature of the workpiece in a field of view of the imaging system, wherein the edge feature comprises a boundary between a region which reflects coaxial light to the imaging system and a region which transmits stage light to the imaging system; (b) holding the edge feature steady at a first position in the field of view and acquiring a first image of the edge using one of the coaxial light and the stage light; (c) holding the edge feature steady at the first position in the field of view and acquiring a second image of the edge using the other of the coaxial light and the stage light; (d) determining a first edge position measurement for a defined portion of the edge feature in the first image; (e) determining a second edge position measurement for the defined portion of the edge feature in the second image; (f) determining a coaxial light edge position correction factor based on a difference between the first edge position measurement and the second edge position measurement; and (g) storing the coaxial light edge position correction factor for correcting subsequent edge position measurements that are based on images acquired using coaxial light.

In some embodiments, the method may further comprise acquiring a subsequent image of an edge feature using the coaxial light; determining an edge position measurement for the edge feature in the subsequent image; and correcting that edge position measurements by adjusting it based on the coaxial light edge position correction factor.

In some embodiments, the method may further comprise performing the steps (a) through (e) a plurality of times, wherein the edge position correction factor is determined in step (f) based on the resulting plurality of first and second edge position measurements. In some embodiments, the steps (a) through (e) are performed a plurality of times using a single edge. In some embodiments, the steps (a) through (e) are performed a plurality of times using a plurality of edges.

In some embodiments, the coaxial light edge position correction factor stored in step (g) is used to correct coaxial light image edge locations measured during run mode operations on various workpieces. In some embodiments, the steps (a) through (g) may be performed in association with a learn mode of a machine vision inspection system using a representative workpiece, such that the coaxial light edge position correction factor is customized for a particular type of workpiece and/or a particular type of edge configuration and/or material on that workpiece.

In some embodiments, the method may be applied based on a user selection in a graphical user interface (GUI) of the machine vision inspection system. In some embodiments, the GUI may include an illumination-dependent correction selector that governs whether to apply the correction method globally, and/or for a particular measurement, etc.

We may define “offset error” to mean an edge location error that has a relatively consistent magnitude, and a consistent polarity relative to the light/dark polarity of an edge that is measured. For some precision machine vision inspection systems (e.g., the QUICK VISION® series referred to previously), an uncorrected edge position measurement using coaxial illumination may have an offset error which is on the order of one pixel unit on the imaging detector, or less (e.g., a sub-pixel error). For various lenses and magnifications this may correspond to a measurement error of a few microns (e.g., corresponding to half a pixel unit), or less. However, using a coaxial light edge position correction factor to correct an edge position measurement as disclosed herein may significantly reduce this offset error (e.g., by a factor of 2-5, or more) such that the coaxial light measurement accuracy approaches the range of manufacturing tolerances of precision reference objects (e.g., on the order of a few tenths of a micron), without actually using such a precision reference object.

It should be appreciated that the methods disclosed herein for determining and applying coaxial light edge position correction factors may provide correction of coaxial light image offset errors with sub-pixel resolution and accuracy in a manner that is easily implemented by an unskilled user of a precision machine vision inspection system, and without the use of a precision reference object. These features are particularly valued by certain users of precision machine vision inspection systems.

DETAILED DESCRIPTION

FIG. 1is a block diagram of one exemplary machine vision inspection system10usable in accordance with methods described herein. The machine vision inspection system10includes a vision measuring machine12that is operably connected to exchange data and control signals with a controlling computer system14. The controlling computer system14is further operably connected to exchange data and control signals with a monitor or display16, a printer18, a joystick22, a keyboard24, and a mouse26. The monitor or display16may display a user interface suitable for controlling and/or programming the operations of the machine vision inspection system10.

The vision measuring machine12includes a moveable workpiece stage32and an optical imaging system34which may include a zoom lens or interchangeable lenses. The zoom lens or interchangeable lenses generally provide various magnifications for the images provided by the optical imaging system34. The machine vision inspection system10is generally comparable to the QUICK VISION® series of vision systems and the QVPAK® software discussed above, and similar state-of-the-art commercially available precision machine vision inspection systems. The machine vision inspection system10is also described in commonly assigned U.S. Pat. Nos. 7,454,053, 7,324,682, 8,111,938 and 8,111,905, which are each incorporated herein by reference in their entireties.

FIG. 2is a block diagram of a control system portion120and a vision components portion200of one embodiment of a machine vision inspection system100including features disclosed herein. As will be described in more detail below, the control system portion120is utilized to control the vision components portion200. The vision components portion200includes an optical assembly portion205, light sources220,230, and240, and a workpiece stage210having a central transparent portion212. The workpiece stage210is controllably movable along X and Y axes that lie in a plane that is generally parallel to the surface of the stage where a workpiece20may be positioned. The optical assembly portion205includes a camera system260, an interchangeable objective lens250, and may include a turret lens assembly280having lenses286and288. Alternatively to the turret lens assembly, a fixed or manually interchangeable magnification-altering lens, or a zoom lens configuration, or the like, may be included. The optical assembly portion205is controllably movable along a Z-axis that is generally orthogonal to the X and Y axes, by using a controllable motor294, as described further below.

A workpiece20, or a tray or fixture holding a plurality of workpieces20, which is to be imaged using the machine vision inspection system100is placed on the workpiece stage210. The workpiece stage210may be controlled to move relative to the optical assembly portion205, such that the interchangeable objective lens250moves between locations on a workpiece20, and/or among a plurality of workpieces20. One or more of a stage light220, a coaxial light230, and a surface light240may emit source lights222,232, or242, respectively, to illuminate the workpiece or workpieces20. The source light is reflected or transmitted as workpiece light255, which passes through the interchangeable objective lens250and the turret lens assembly280and is gathered by the camera system260. The image of the workpiece(s)20, captured by the camera system260, is output on a signal line262to the control system portion120. The light sources220,230, and240may be connected to the control system portion120through signal lines or busses221,231, and241, respectively. To alter the image magnification, the control system portion120may rotate the turret lens assembly280along axis284to select a turret lens, through a signal line or bus281.

In various exemplary embodiments, the optical assembly portion205is movable in the vertical Z-axis direction relative to the workpiece stage210using a controllable motor294that drives an actuator, a connecting cable, or the like, to move the optical assembly portion205along the Z-axis to change the focus of the image of the workpiece20captured by the camera system260. The term Z-axis, as used herein, refers to the axis that is intended to be used for focusing the image obtained by the optical assembly portion205. The controllable motor294, when used, is connected to the input/output interface130via a signal line296.

As shown inFIG. 2, in various exemplary embodiments, the control system portion120includes a controller125, the input/output interface130, a memory140, a workpiece program generator and executor170, and a power supply portion190. Each of these components, as well as the additional components described below, may be interconnected by one or more data/control buses and/or application programming interfaces, or by direct connections between the various elements.

The input/output interface130includes an imaging control interface131, a motion control interface132, a lighting control interface133, and a lens control interface134. The motion control interface132may include a position control element132a, and a speed/acceleration control element132b. However, it should be appreciated that in various exemplary embodiments, such elements may be merged and/or indistinguishable. The lighting control interface133includes lighting control elements133a-133n, which control, for example, the selection, power, on/off switch, and strobe pulse timing if applicable, for the various corresponding light sources of the machine vision inspection system100.

The memory140includes an image file memory portion141, a workpiece program memory portion142that may include one or more part programs, or the like, and a video tool portion143. The memory140may also include an illumination correction factor portion140cf, which stores illumination-dependent edge position correction factors (e.g., coaxial light edge position correction factors), as described in greater detail below. The video tool portion143includes tool portion143aand other similar tool portions (˜143m), which determine the GUI, image processing operation, etc., for each of the corresponding tools. The video tool portion143also includes a region of interest generator143xthat supports automatic, semi-automatic and/or manual operations that define various ROIs that are operable in various video tools included in the video tool portion143. One exemplary edge detection video tool is explicitly represented for convenience of description, an edge detection video tool143ed. It should be appreciated that other video tools may include similar edge detection features and operations within their scope. The edge detection video tool143edmay include an illumination-dependent correction mode portion143idc, which applies illumination-dependent edge position correction factors (e.g., coaxial light edge position correction factors) to substantially reduce or eliminate illumination-dependent offset errors, as described in greater detail below. Therefore, in various embodiments, the illumination-dependent correction mode portion143idcmay be considered as part of each individual video tool, or as a general feature of the video tool portion143which is applicable to a variety of different video tools.

In general, the memory portion140stores data usable to operate the vision system components portion200to capture or acquire an image of the workpiece20such that the acquired image of the workpiece20has desired image characteristics. The memory portion140may also store inspection result data, may further store data usable to operate the machine vision inspection system100to perform various inspection and measurement operations on the acquired images (e.g., implemented, in part, as video tools), either manually or automatically, and to output the results through the input/output interface130. The memory portion140may also contain data defining a graphical user interface operable through the input/output interface130.

The signal lines or busses221,231, and241of the stage light220, the coaxial light230, and the surface light240, respectively, are all connected to the input/output interface130. The signal line262from the camera system260and the signal line296from the controllable motor294are connected to the input/output interface130. In addition to carrying image data, the signal line262may carry a signal from the controller125that initiates image acquisition.

One or more display devices136(e.g., the display16ofFIG. 1) and one or more input devices138(e.g., the joystick22, keyboard24, and mouse26ofFIG. 1) can also be connected to the input/output interface130. The display devices136and input devices138can be used to display a user interface, which may include various graphical user interface (GUI) features that are usable to perform inspection operations, and/or to create and/or modify part programs, to view the images captured by the camera system260, and/or to directly control the vision system components portion200.

In various exemplary embodiments, when a user utilizes the machine vision inspection system100to create a part program for the workpiece20, the user generates part program instructions either by explicitly coding the instructions automatically, semi-automatically, or manually, using a workpiece programming language, and/or by generating the instructions by operating the machine vision inspection system100in a learn mode to provide a desired image acquisition training sequence. For example, a training sequence may comprise positioning a workpiece feature in the field of view (FOV), setting light levels, focusing or autofocusing, acquiring an image, and providing an inspection training sequence applied to the image (e.g., using video tools). The learn mode operates such that the sequence(s) are captured or recorded and converted to corresponding part program instructions. These instructions, when the part program is executed, will cause the machine vision inspection system to reproduce the trained image acquisition and inspection operations to automatically inspect a workpiece or workpieces matching the workpiece used when creating the part program.

These analysis and inspection methods that are used to inspect features in a workpiece image are typically embodied in various video tools included in the video tool portion143of the memory140. Many known video tools, or “tools” for short, are included in commercially available machine vision inspection systems, such as the QUICK VISION® series of vision systems and the associated QVPAK® software, discussed above.

FIG. 3shows a cross section view300A of features on a representative workpiece aligned with a corresponding set of signal intensity profiles300B along a scan line in images of a workpiece edge feature320associated with edge location operations. The set of signal intensity profiles300B depict a difference between an edge location ELsp detected in stage light image, and an edge location ELcp detected in coaxial light image, as described in greater detail below.

The workpiece edge feature320comprises an opaque portion321that reflects coaxial source light232toward the imaging system and blocks stage source light222, and a transmissive portion322(e.g., a transparent substrate, a bore or simply a region beyond an edge where workpiece material is absent) that transmits stage source light222toward the imaging system. In other words, coaxial light is the main contributor to the workpiece light255that forms the image of the opaque portion321, and stage light is the main contributor to the workpiece light255that forms the image of the transmissive portion322. The set of signal intensity profiles300B shows a coaxial light image profile CP and a stage light image profile SP. The coaxial light image profile CP corresponds to an edge detection scan line (e.g., along a line of image detector pixels) when the workpiece edge feature320is illuminated with the coaxial light232from the coaxial light230to form a coaxial light image of the edge feature320. The stage light image profile SP corresponds to an edge detection scan line when the workpiece edge feature320is illuminated with the stage light222from the stage light220to form a stage light image of the edge feature320.

The coaxial light image profile CP indicates an edge location ELcp that is determined based on the data of the coaxial light image profile CP (e.g., as determined by applying a known type of edge detection algorithm, such as a maximum gradient edge detector that is used in the video tools of the machine vision inspection system.) Similarly, the stage light image profile SP indicates an edge location ELsp that is determined based on the data of the stage light image profile SP (e.g., as determined by applying a known type of edge detection algorithm that is used in the video tools of the machine vision inspection system). There is a difference8equal to (ELsp-ELcp) between the detected edge locations, described below.

Illumination-dependent edge location errors at the sub-pixel and/or sub-micron level may be difficult to detect and/or characterize. Prior art methods have used precision reference objects to determine offset error correction factors. However, since the fabrication tolerances and/or thermal expansion of reference objects may be of the same order as such illumination-dependent edge location errors, such prior methods are undesirable for their use of reference objects as well as for their complexity, which is beyond the skill of many users of machine vision inspection systems. Furthermore, some prior art methods may not be applicable to reduce sub-pixel level errors, due to lack of consideration of the limited detector resolution.

The inventors have found that stage light systems may provide images that yield accurate edge location results (e.g., within the fabrication uncertainty of precision reference objects). Stage light systems that collimate light from a light generator to illuminate a workpiece image may provide particularly accurate edge locations and may exhibit relatively low variation between workpieces. In some embodiments, stage light systems that also pass the collimated light through a diffuser plate may similarly provide accurate edge locations. It will be appreciated that for various types of workpieces, the light that forms a stage light “shadow” image is generally not reflected from a surface, or an edge radius, or the like. Therefore, stage light images may be relatively unaffected by material and edge profile variations that affect reflected light images. Methods disclosed herein measure an edge using the stage light and use that measurement as an accurate reference measurement. That same edge may be measured using the coaxial light, and the difference in the edge location (the difference8, outlined above) may be stored and used as a coaxial light edge position correction factor. In some embodiments, it is preferable that the edge not be moved between the acquisition of images which are used to determine the difference, in order to eliminate errors due to detector and/or optical imperfections and/or motion system measurement errors. The inventors have found that coaxial light images may exhibit edge location errors that are as much as ten times larger than location measurement errors using stage light images. Determining and applying a coaxial light edge position correction factor as disclosed herein has been shown to reduce coaxial light edge location errors by approximately two to five times, or more, for a variety of applications.

It should be appreciated that a coaxial light edge position correction factor has a particular polarity; that is, the offset error is either toward the brighter side of an edge or the darker side of an edge. For many edges the coaxial light image produces an apparent location of the edge which includes an offset error toward the brighter side of the edge. Thus, in such cases, the coaxial light edge position correction factor is applied to correct the edge location to be farther toward the darker side of the edge. For this reason, in some embodiments, the coaxial light edge position correction factor comprises both a magnitude and a polarity such that it may be applied globally, and the operations of the illumination-dependent correction mode portion may include determining the polarity of the edge in the image and applying the correction factor to correct the edge location with the proper polarity relative to the image. In various embodiments, the coaxial light edge position correction factor is also determined and applied along a direction that is perpendicular to an edge.

As previously indicated, to reduce sub-pixel level offset errors, consideration of the limited detector resolution may be required.FIG. 4shows a field of view400of a machine vision inspection system which includes a workpiece including edge features420a-420dwhich have a configuration which may be advantageous for determining a coaxial light edge position correction factor with very high accuracy.

The field of view400includes a square opaque portion421and a transmissive portion422, which may operate as previously described for the opaque portion321and transmissive portion322ofFIG. 3. The square shape is exemplary and not limiting. The illustrated regions of interest ROIa, ROIb, ROIc, and ROId are associated with respective edge location video tools143edwhich are configured to measure various edge features420a-420d. A first instance of the video tools may measure their respective edges using a stage light image, and a second instance of the video tools may measure their respective edges using a coaxial light image. In some cases, it is advantageous to measure the difference of an edge location using coaxial and stage light a plurality of times, and/or at a plurality of locations to determine a coaxial light edge position correction factor based on an average value that is less likely to include local or temporary sources of measurement noise arising from irregularities in the optics or detector or vibration or the like.

In addition, it will be appreciated that the edges in the regions of interest ROIa-ROId are rotated with respect to the row and column directions of the detector. Thus, the various scan lines SL sample the signal intensity profile with a different relationship between the edge and the pixels along each scan line. The edge location is determined from the plurality of scan lines in the ROI. In effect, this is substantially similar to sampling the edge signal intensity profile with a higher density sampling than the detector pixel spacing and allows the edge position to be determined with higher resolution. This may be important when attempting to correct sub-pixel offset errors.

In addition, if the square opaque portion421is an object having a known dimension, the distance between stage light measurements of the opposing sides of the square may be compared to the known dimension of the square to verify that the stage light measurements have a negligible offset error, if desired.

FIG. 5is a flow diagram500outlining a method and routine for operating a machine vision inspection system to determine a coaxial light edge position correction factor used to provide illumination-dependent corrections for subsequent edge location measurements.

At a block510, a machine vision inspection system is provided, which comprises an imaging system (e.g., the optical assembly portion205), a workpiece stage (e.g., the workpiece stage210), a coaxial illumination portion (e.g., coaxial light230) which projects coaxial light (e.g., the coaxial source light232) from an objective lens (e.g., the objective lens250) of the imaging system toward the workpiece stage, a stage light illumination portion (e.g., the stage light220) which projects stage light (e.g., the stage source light222) from the workpiece stage toward the imaging system, and a control system (e.g., the control system portion120).

At a block520, a workpiece (e.g., the workpiece20) is positioned on the workpiece stage with an edge feature of the workpiece (e.g., the edge feature320or420) in a field of view (e.g., the field of view400) of the imaging system, wherein the edge feature comprises a boundary between a region which reflects coaxial light (e.g., the opaque portion321or421) to the imaging system and a region which transmits stage light (e.g., the reflective portion322or422) to the imaging system.

At a block530, the edge feature is held steady at a first position in the field of view and a first image of the edge is acquired using one of the coaxial light and the stage light.

At a block540, the edge feature is held steady at the first position in the field of view and a second image of the edge is acquired using the other of the coaxial light and the stage light.

At a block550, a first edge position measurement is determined for a defined portion of the edge feature in the first image. For example, the first edge position measurement may be determined based on analysis of a first one of the coaxial light image profile CP or the stage light image profile SP, or a plurality of such profiles at respective scan lines across the edge in the first image.

At a block560, a second edge position measurement is determined for the defined portion of the edge feature in the second image. For example, the second edge position measurement may be determined based on analysis of the other of the coaxial light image profile CP or the stage light image profile SP, or a plurality of such profiles at respective scan lines across the edge in the first image.

At a block570, a coaxial light edge position correction factor is determined based on a difference between the first edge position measurement and the second edge position measurement (e.g., based on the difference6).

At a block580, the coaxial light edge position correction factor is stored for correcting subsequent edge position measurements that are based on images acquired using coaxial light. In the exemplary embodiment ofFIG. 2, the coaxial light edge position correction factor is stored in the illumination correction factor portion140cfof the memory140.

In some embodiments or applications, the edge position correction factor may be used for adjusting a measurement determined in an analogous manner to that of the block550or560using coaxial light. In such a case the method may comprise additional steps of: acquiring a subsequent image of an edge feature using the coaxial light, determining an edge position measurement for the edge feature in the subsequent image, and correcting that edge position measurement by adjusting it based on the coaxial light edge position correction factor. The steps may be implemented via the illumination-dependent correction mode portion143idcofFIG. 2.

In some embodiments, the method and routine shown in the flow diagram500comprises performing the steps at blocks510through560repeatedly for an edge, or for a plurality of edges and/or different edge orientations, and then at the block570the coaxial light edge position correction factor is determined based on the resulting plurality of respective first and second edge position measurements, for example, based on an average of the differences of the resulting respective first and second edge position measurements, or as previously outlined with reference toFIG. 4.

In some embodiments, or in some part programs, a coaxial light edge position correction factor is determined based on a desired workpiece (e.g., a calibration object or a standard workpiece) and is applied globally. That is, it is used to correct coaxial light image edge locations measured during run mode operations on various workpieces and/or edges.

In some embodiments, or when creating certain part programs, a coaxial light edge position correction factor may be determined for a particular representative workpiece during learn mode (e.g., using the method and routine shown in the flow diagram500) and applied globally for coaxial images of that workpiece during run mode operations on similar workpieces. In another case, in some embodiments, or when creating certain part programs, a coaxial light edge position correction factor may be determined for a particular edge configuration on a representative workpiece during learn mode and applied only to coaxial images of that particular edge configuration during run mode operations on similar workpieces. Compared to stage light images, the edge location in coaxial light images is more sensitive to the particular materials and configuration of an edge (e.g., including its thickness, surface finish, shape, and the like). Therefore, it will be appreciated that applying a coaxial light edge position correction factor globally in machine vision inspection system may reduce coaxial image edge location errors to a first degree. A further degree of error reduction may be achieved with a part program that performs run mode operations that include applying a workpiece-specific coaxial light edge position correction factor that is determined during learn mode operations using a representative workpiece. A further degree of error reduction may be achieved with a part program that performs run mode operations that include applying an edge-specific coaxial light edge position correction factor (e.g., for a specific instance of a video tool on a specific edge) that is determined during learn mode operations for that specific edge and/or video tool instance on a representative workpiece.

In some embodiments, the method(s) disclosed herein for correcting coaxial light image edge locations based on a coaxial light edge position correction factor may be applied (or not applied) based on a user selection in a graphical user interface (GUI) of the machine vision inspection system. The GUI may be implemented using the control system of the machine vision inspection system. In some embodiments, the GUI may include an illumination-dependent correction selector (e.g., a check box or radio button) included in a video tool parameter listing/editing box included in the GUI. The GUI may include a global illumination-dependent correction selector (e.g., a check box in default listing/editing box) that determines whether the correction method will be globally applied to edge detection in all coaxial light images within a part program, and/or a tool-specific illumination-dependent correction selector (e.g., a check box in tool parameter listing/editing box for a particular instance of a video tool applied to a coaxial light image) that determines whether the correction method will be applied to edge detection in that particular instance of the video tool within a part program. In some embodiments, respective coaxial light edge position correction factors may be determined for different types of edge features (e.g., a thick copper edge, a thin gold edge, a thin chrome edge, etc.) and the GUI may include a selector or selectors that allows a user to select a particular one of the respective correction factors to be implemented for a particular workpiece or a particular instance of a video tool.