Low Distortion vs Standard Machine Vision Lens: Which One Do You Need for Measurement, Gauging and Positioning?

A machine vision image can look perfectly sharp and still produce inaccurate measurements. The reason is simple: image sharpness and geometric accuracy are not the same thing.

For industrial inspection applications such as dimensional measurement, gauging, robotic positioning, edge location and coordinate verification, the lens must do more than resolve fine detail. It also needs to reproduce the geometry of the object predictably across the camera sensor.

This is where lens distortion becomes important.

A standard Machine Vision Lens can be entirely suitable for presence detection, barcode reading, OCR, general inspection and many defect-detection applications. A low distortion Machine Vision Lens becomes more important when the vision system uses image coordinates to calculate real dimensions or positions.

The buying decision should therefore not be based on the assumption that low distortion is always better. The more useful question is whether distortion can change the result your vision system is trying to calculate.

If the camera only needs to decide whether a component exists, a small geometric shift near the image edge may have little practical consequence. If the same camera is measuring a hole diameter, locating a robotic pickup position or checking whether a machined feature is within tolerance, that shift can become part of the measurement error.

Kyptec Automation® provides a broad Machine Vision Lens range covering different focal lengths, sensor formats and optical resolution classes for industrial imaging. The correct choice should be made by considering both image detail and geometric accuracy rather than choosing a lens from focal length alone.

What Is Lens Distortion in Machine Vision?

Lens distortion is a geometric imaging error in which the position of image points differs from the position expected from an ideal perspective projection.

The lens can still be sharply focused.

Fine details can still look clear.

The problem is that straight lines or object coordinates may be shifted slightly depending on where they appear within the image.

In a perfectly ideal rectilinear lens, a straight physical line remains straight in the image and image magnification follows the expected geometric relationship across the complete frame.

Real lenses are not perfect.

The amount and type of distortion depend on optical design, focal length, sensor coverage, working distance and other factors.

For many inspection tasks, the distortion is small enough that it does not materially affect the result. For precision measurement and coordinate based applications, it needs to be understood and controlled.

Barrel Distortion Explained

Barrel distortion occurs when image magnification decreases toward the edges of the frame.

Straight lines near the edge appear to bow outward.

A rectangular object can appear slightly expanded in the middle and compressed toward the corners.

The effect is commonly associated with wider angle optical designs because producing a large field of view while preserving perfectly rectilinear geometry can be challenging.

In ordinary visual inspection, mild barrel distortion may be acceptable.

In dimensional gauging, however, an object of identical physical size can appear to occupy a slightly different number of pixels depending on where it lies within the field.

This means measurement results can vary with object position unless the distortion is sufficiently low or accurately calibrated.

Pincushion Distortion Explained

Pincushion distortion produces the opposite geometric tendency.

Magnification increases toward the image edges, causing straight lines to bend inward.

Again, the image can remain optically sharp.

The issue is coordinate accuracy rather than focus.

If a measurement system assumes that every pixel represents the same object distance everywhere across the image, pincushion distortion can introduce systematic error.

This is why low distortion industrial lenses are particularly valuable when objects can appear at different positions within a wide field of view.

Low Distortion Does Not Mean Zero Distortion

No practical lens should be assumed to have absolutely zero distortion simply because it is described as low distortion.

The phrase means that geometric distortion has been controlled to a level suitable for the intended optical design.

For high accuracy measurement, the actual lens should still be calibrated within the complete camera system.

Camera alignment, object position, working distance and perspective can all contribute additional geometric error beyond the lens itself.

Low distortion reduces one important source of error.

Calibration handles the residual behaviour of the complete imaging system.

Standard Machine Vision Lens vs Low Distortion Machine Vision Lens

A standard Machine Vision Lens is typically optimized around a practical balance of field of view, resolution, sensor compatibility, aperture and cost.

It can perform extremely well in industrial inspection.

A low distortion Machine Vision Lens places additional emphasis on preserving geometric relationships across the image.

For general defect detection, the system may primarily need sufficient contrast and resolution.

For OCR, it may need readable character strokes.

For barcode inspection, it may need clear code modules.

For dimensional gauging, the lens must preserve where those edges appear.

That is the key difference.

The low distortion requirement becomes stronger as the software moves from recognizing what an object is toward calculating exactly where its boundaries are.

When Is a Standard Machine Vision Lens Enough?

A standard Machine Vision Lens can be the correct choice when the inspection decision is relatively insensitive to geometric displacement.

Consider an application that checks whether a cap is fitted onto a container.

The software may simply look for a characteristic shape or region.

A small amount of lens distortion is unlikely to change the pass or fail result.

The same can apply to component presence verification, label recognition, basic assembly inspection, general OCR and many barcode applications.

If the camera is not being used as a precision measuring instrument, paying specifically for extremely low geometric distortion may not provide significant operational value.

The lens should still have adequate optical quality, resolution and sensor coverage.

The point is that geometric fidelity does not need to dominate the purchasing decision.

When Should Low Distortion Become a Priority?

Low distortion becomes more important when numerical dimensions or image coordinates directly affect the machine decision.

Typical examples include diameter measurement, gap measurement, width measurement, hole spacing, edge-to-edge distance, component alignment, positional inspection, robotic coordinate generation, precision gauging and repeated measurement at different locations in the image.

If the object can appear anywhere in the field, geometric consistency becomes particularly valuable.

A measurement system should ideally give the same dimensional result whether the component is centred or located near the edge of the permitted inspection area.

The closer your tolerance becomes to the amount of geometric error introduced by the lens, the more important distortion performance becomes.

Why Measurement Applications Are More Sensitive to Distortion

Suppose a vision system measures the width of a manufactured component.

The software identifies the left edge and right edge and calculates the distance between them in pixels.

A calibration factor then converts that pixel distance into millimetres.

If image scale changes slightly across the frame because of lens distortion, the same 20 mm object can produce different pixel widths at different image positions.

That creates a systematic measurement error.

The image can still look excellent to a human observer.

This is why measurement systems need to be evaluated numerically rather than visually.

A lens suitable for inspection is not automatically suitable for precision gauging.

Worked Example: How a Small Distortion Percentage Can Affect Measurement

Consider an illustrative application measuring a 100 mm feature.

Suppose the imaging geometry introduces a 0.5 percent geometric error at a particular image location.

An error of 0.5 percent across 100 mm corresponds to:

100 × 0.005 = 0.5 mm.

If the acceptable manufacturing tolerance is ±2 mm, that error might be manageable depending on the rest of the system.

If the required tolerance is ±0.1 mm, a potential 0.5 mm geometric contribution is unacceptable.

The important lesson is that “low distortion” has meaning only relative to the required measurement tolerance.

A specification that is more than adequate for one gauging application may be insufficient for another.

Distortion Error Should Be Compared with the Measurement Tolerance

One of the strongest ways to decide whether you need a low distortion lens is to build a measurement error budget.

Suppose a dimensional system must measure within ±0.2 mm.

Lens distortion is only one potential contributor.

Camera calibration may contribute error.

Edge detection may contribute error.

Mechanical vibration may contribute error.

Object positioning may contribute error.

Perspective may contribute error.

If any single source consumes most of the available ±0.2 mm tolerance, the system has little margin left for the others.

This is why a low distortion Machine Vision Lens becomes increasingly valuable as required measurement tolerance tightens.

Low Distortion Lens for Machine Vision Gauging

Machine vision gauging converts image measurements into physical dimensions.

Common applications include checking component width, diameter, slot dimensions, gap, spacing, alignment and tolerance limits.

For these tasks, stable geometric mapping is important.

A suitable industrial lens should provide enough resolution to locate edges clearly and sufficiently controlled distortion that the mapping between image coordinate and object coordinate remains predictable.

Kyptec Automation® machine vision lenses are designed for industrial imaging applications including dimensional analysis and measurement. For example, Kyptec Automation® KL-1216 25 mm 10 MP Machine Vision Lens is a C mount lens for compatible 1 inch systems, while Kyptec Automation® KL-1218 35 mm 10 MP Machine Vision Lens provides a longer 35 mm focal length within the same broad resolution and sensor class.

The correct model still depends on field of view and working distance. Distortion performance should be considered after the basic imaging geometry has been defined.

Low Distortion Lens for Positioning Applications

Positioning systems often use the camera to calculate where an object is located.

The resulting X and Y coordinates may be passed to a robot, actuator or machine controller.

In this situation, lens distortion can change apparent object position depending on where the target appears in the image.

A component near the centre may be localized accurately.

The same component near the edge may show a larger coordinate offset if distortion is not accounted for.

Calibration can compensate for repeatable geometric distortion, but a lower distortion optical system generally reduces the amount of correction required and can improve system robustness.

For positioning applications, buyers should therefore consider not only image sharpness but coordinate stability across the usable field of view.

Why Robotic Pick and Place Can Be Sensitive to Lens Distortion

A robot vision system often converts camera coordinates into machine coordinates.

If a component appears at image coordinate X1, Y1, the calibration determines where the robot should move.

If optical distortion shifts the apparent position of objects near the edges, the calculated robot position can also shift.

This can matter when grippers have limited alignment tolerance or when components are small.

A large tray inspected by one camera can be particularly demanding because parts may appear from the centre all the way to the sensor corners.

Reducing distortion and performing proper geometric calibration work together to improve coordinate consistency.

Does Lens Calibration Completely Remove Distortion?

Calibration can correct a substantial amount of repeatable geometric distortion.

The software observes a known calibration pattern and calculates how image coordinates deviate from ideal geometry.

A mathematical model can then transform the distorted image or correct measurement coordinates.

However, calibration should not be viewed as an unlimited substitute for suitable optics.

Strong distortion requires larger corrections.

Corrected image regions may need interpolation.

Calibration remains valid only while the camera, lens and mechanical geometry remain sufficiently stable.

If working distance, focus, lens setting or camera alignment changes significantly, recalibration may be required.

Starting with lower optical distortion therefore reduces dependence on large software corrections.

Is Calibration Still Necessary with a Low Distortion Lens?

For precision measurement, usually yes.

Low distortion means the lens contributes less geometric error.

Calibration establishes the actual mapping between image pixels and physical space in the installed system.

Even an excellent lens cannot compensate for a camera mounted at a slight angle or an object plane that is not where the calibration assumes it to be.

A properly designed measurement system therefore uses both good optics and good calibration.

The lens reduces inherent geometric deviation.

Calibration accounts for the remaining system geometry.

Why Distortion Becomes More Noticeable Near Image Edges

Optical rays reaching the outer portions of the sensor travel through a more challenging region of the lens system.

Many aberrations and geometric deviations become harder to control farther from the optical axis.

This is one reason an object can measure correctly near the centre but produce a different result near the edge when the optical system has not been properly corrected or calibrated.

A simple practical test is to image a known reference object in several locations across the field.

If the measured dimension changes significantly as the reference moves from centre to corner, geometric effects need to be investigated.

This test can reveal lens distortion, calibration problems or perspective issues.

Sensor Size Can Increase the Importance of Edge Distortion

A larger sensor uses a greater portion of the lens image circle.

That means it reaches farther into the outer optical field.

If the camera uses a 1 inch or 1.1 inch sensor, edge performance can therefore become more important than on a smaller sensor using only the central image region.

This is one reason lens sensor-format compatibility should never be considered purely as a question of avoiding black corners.

The lens also needs to maintain suitable geometric and resolving performance across the area the camera actually uses.

Kyptec Automation® offers lenses for different sensor classes, including Kyptec Automation® KL-1216 and Kyptec Automation® KL-1218 for compatible 1 inch 10 MP systems and Kyptec Automation® KL-1240 25 mm 25 MP Machine Vision Lens for a larger high resolution format.

Focal Length and Distortion Are Related but Not Identical

Shorter focal lengths often face greater challenges in maintaining rectilinear geometry because they capture a wider field.

However, you should not assume that every short focal length lens has unacceptable distortion or that every long focal length lens has negligible distortion.

Optical design matters.

A well-designed wide-angle Machine Vision Lens can provide controlled geometric performance.

A longer focal length lens can still require calibration for precision measurement.

Focal length should therefore be selected according to required field of view and working distance first.

Distortion should then be evaluated within the focal length range appropriate for the machine.

Can a Longer Focal Length Reduce Distortion Problems?

Sometimes a longer focal length can make the optical geometry easier to manage, particularly if it allows the same field to be captured from a greater working distance with less extreme wide-angle imaging.

However, it is not a universal solution.

Changing focal length can change camera placement, perspective, mechanical clearance and depth of field.

If the machine has enough space, a longer working distance and less aggressive field angle can sometimes be advantageous for measurement.

The decision should be made from complete system geometry rather than choosing a longer focal length solely because distortion is a concern.

Kyptec Automation® KL-1232 is a 50 mm 10 MP Machine Vision Lens for compatible 2/3 inch systems and represents one longer focal length option when the field of view and working distance require it.

Distortion vs Perspective Error

Lens distortion and perspective distortion are not the same thing.

Lens distortion comes from the optical mapping of the lens.

Perspective error comes from the relative geometry between camera and object.

If the camera is tilted relative to a flat rectangular object, one side can appear larger than the other even when the lens itself has extremely low optical distortion.

A low distortion lens will not fix incorrect camera alignment.

For measurement applications, the optical axis and measurement plane should be arranged carefully.

This is especially important when the camera is positioned at an angle because of mechanical constraints.

Distortion vs Parallax

Parallax occurs when object features lie at different depths and their apparent relative positions change with viewing geometry.

A low distortion lens does not remove ordinary perspective parallax.

If one component is physically higher than another, their image positions can change relative to each other depending on camera placement.

For simple flat-part gauging, this may not be an issue.

For three-dimensional assemblies, it can become significant.

When very high measurement accuracy is required across varying heights, specialized optical approaches may need to be evaluated.

This is another reason not to treat “low distortion” as a solution to every geometric measurement problem.

Why Resolution Still Matters in a Low Distortion Lens

A geometrically accurate image is not useful for precision measurement if the edges themselves are too blurry to locate reliably.

Measurement requires both geometric fidelity and sufficient optical resolution.

Suppose a lens produces almost perfect straight-line geometry but the image edges spread across many pixels.

The software cannot determine the exact boundary consistently.

Conversely, an extremely sharp lens with large uncorrected geometric distortion can locate the edge precisely but at the wrong geometric position.

A strong measurement optical system therefore needs both adequate resolution and controlled distortion.

This is why Kyptec Automation® offers Machine Vision Lenses across different optical resolution classes rather than treating low distortion as the only requirement.

Worked Example: Centre Measurement vs Edge Measurement

Suppose a calibration object has a known width of 50.00 mm.

At the centre of the image, the vision system measures 50.02 mm.

Near the left edge, it measures 50.31 mm.

Near the right edge, it measures 50.29 mm.

The variation is systematic and changes with image position.

This pattern suggests geometric mapping needs attention.

Possible contributors include lens distortion, insufficient calibration, camera angle or use of the lens outside its optimal image region.

Simply increasing camera megapixels will not solve this kind of problem.

The system needs better geometric control.

Worked Example: When Standard Distortion Is Acceptable

Consider a machine checking whether a circular washer is present in a fixture.

The fixture area is large and the software only needs to verify that a circular feature exists within a defined region.

Suppose the washer appears near different parts of the image.

Moderate geometric distortion may slightly change its apparent shape or location, but the algorithm still recognizes it easily.

In this case, the inspection does not justify choosing optics primarily around extremely low distortion.

Resolution, field of view, sensor compatibility and cost may be more important.

This is a good example of why standard industrial optics remain appropriate for many machine vision applications.

Worked Example: When Low Distortion Becomes Worth Paying For

Now consider a system measuring the gap between two machined surfaces.

The acceptable gap tolerance is only ±0.05 mm.

Parts can appear anywhere across a wide inspection field.

If image scale changes measurably from centre to edge, the lens contributes directly to measurement uncertainty.

Here, a low distortion optical design and careful calibration become valuable.

The additional optical requirement is justified because the application result depends on accurate geometry.

The same logic applies to precision component location, hole spacing and automated gauging.

How to Test Lens Distortion Before Final Machine Approval

Use a known calibration target or precisely manufactured reference pattern.

Place it at the real working distance.

Capture the complete field.

Check whether straight reference lines remain geometrically consistent.

Measure known distances near the centre and at several edge positions.

Repeat the test after focusing and aperture adjustments are finalized.

If the application uses different product heights, test those heights as well.

The final lens should be evaluated in the same mechanical and optical configuration that will be used in production.

A datasheet can narrow the choice, but system-level validation confirms whether the actual measurement tolerance is achieved.

How Aperture Can Influence Measurement Performance

Aperture does not primarily determine geometric distortion, but it affects edge sharpness and depth of field.

If the aperture is too wide, depth of field may be insufficient and some measurement edges can become soft.

If the aperture is closed excessively, diffraction can reduce fine detail.

The best aperture is therefore one that keeps the measurement plane acceptably sharp while preserving sufficient optical resolution.

Once the aperture is selected, the system should be calibrated under the same operating condition whenever high accuracy is required.

Changing optical settings after calibration can change image behaviour enough to justify recalibration.

Why Lens Focus Should Be Locked After Calibration

Measurement systems depend on repeatability.

Changing focus can slightly change effective magnification and image geometry.

Even if the difference appears visually insignificant, it can influence calibrated measurement results.

After focus has been optimized, the lens should remain mechanically stable.

For OEMs producing repeated machines, the camera, lens, working distance and focus procedure should be documented as part of the inspection configuration.

This makes replacement and commissioning more consistent.

Low Distortion for High Resolution Cameras

High resolution cameras make geometric behaviour more visible because the sensor records many more image coordinates across the field.

A small physical displacement may correspond to several pixels.

This does not mean every high resolution camera automatically requires a special low distortion lens.

It means the lens needs to match the accuracy target of the system.

For demanding larger-format imaging, Kyptec Automation® KL-1244 50 mm 25 MP Machine Vision Lens represents one high-resolution C mount configuration when its focal length and sensor coverage suit the application.

The final measurement suitability should still be established through the actual error budget and system calibration.

Frequently Asked Questions About Low Distortion and Standard Machine Vision Lenses

1. How can I tell whether lens distortion is causing my measurement error?

Measure a calibrated reference object at several positions across the camera field. If the same physical dimension changes systematically as it moves from centre toward the edges, geometric mapping is a likely contributor. Check calibration and camera alignment as well because they can produce similar symptoms.

2. Can a lens be very sharp and still have too much distortion for gauging?

Yes. Sharpness and distortion describe different optical characteristics. A lens can resolve an edge very clearly while placing that edge at a geometrically shifted image coordinate. Precision gauging requires both adequate edge resolution and predictable geometry.

3. Do I need a low distortion Machine Vision Lens if every part is always centred?

The requirement may be less demanding when the same small central sensor region is always used because the centre usually experiences less geometric deviation than the extreme field. However, required tolerance still determines whether the residual distortion is acceptable. Validate measurement accuracy within the actual region of interest.

4. Why does measurement accuracy get worse near the corners of my image?

Possible causes include lens distortion, reduced edge resolution, image-circle limitations, perspective geometry or calibration that does not model the full field accurately. Compare a known reference at several positions to identify whether the error follows image location.

5. Can I crop the centre of the image instead of buying a lower distortion lens?

Sometimes. If the central image region provides adequate field of view and measurement accuracy, using only that region can avoid more challenging outer optical areas. The tradeoff is reduced usable field. If the entire sensor is required, a better-matched lens or stronger calibration may be necessary.

6. Does lower distortion improve robot positioning accuracy?

It can improve the consistency of image coordinates across the field, which is useful for robot calibration and pick coordinates. Robot accuracy also depends on camera calibration, mechanical calibration, object height, gripper repeatability and transformation accuracy. A low distortion lens reduces one part of the total positioning error.

7. Is distortion more important for X-Y positioning or dimensional measurement?

It can matter strongly for both. Dimensional measurement uses the spacing between image points, while X-Y positioning uses absolute or transformed coordinates. If distortion varies across the field, both distance and position can be affected. The acceptable level depends on the tolerance of the particular machine.

8. Can software calibration make a standard Machine Vision Lens suitable for measurement?

Often, yes, when distortion is stable and within a range that can be modelled accurately. Whether this is sufficient depends on the required tolerance. A low distortion lens can reduce the magnitude of correction and provide more margin, especially in demanding measurement systems.

9. Does changing working distance affect distortion calibration?

It can. Changing object distance changes magnification and imaging geometry, and the calibrated mapping may no longer represent the new setup accurately. Precision systems should normally be calibrated at the same working distance and focus configuration used during production.

10. Should I recalibrate after replacing a Machine Vision Lens with the same focal length?

For precision measurement or positioning, yes. Two lenses with the same nominal focal length can have small differences in effective geometry, distortion and focusing position. Recalibration is the safer approach whenever a measurement-system lens is replaced.

11. Is a longer focal length always better for dimensional gauging?

No. A longer focal length can be useful when it suits the required working distance and field of view, but measurement quality depends on distortion, resolution, alignment and calibration as well. Choose focal length from the optical geometry first, then evaluate measurement performance.

12. Does low distortion matter for checking hole-to-hole spacing?

Yes, particularly when holes span a large portion of the image or the required spacing tolerance is small. Distortion can alter apparent coordinate spacing across the sensor. A low distortion Machine Vision Lens combined with calibration can improve repeatability for this type of gauging application.

13. How do I decide whether the distortion specification is good enough for my tolerance?

Translate the expected geometric error into object-side units and compare it with the total allowable measurement error. Remember that lens distortion is only one contributor. Leave enough error budget for calibration, edge detection, mechanical variation and other system factors.

14. Can low distortion improve repeatability even if absolute accuracy is calibrated?

Yes. Reducing the amount of geometric correction required can make the system less sensitive to calibration errors and small setup changes. Absolute accuracy still depends on calibration, while repeatability depends on the stability of the complete optical and mechanical system.

15. What details should I provide when requesting a Machine Vision Lens for precision gauging?

Provide the camera model, sensor size, camera resolution, field of view, working distance, focal length if already calculated, measurement range, required tolerance, object height variation and whether measurements occur across the full frame or only near the centre. These details can be used to narrow the Kyptec Automation® Machine Vision Lens range according to the actual measurement requirement instead of selecting a lens only from focal length or megapixel rating.

How to Choose Between Low Distortion and Standard Machine Vision Optics

Begin with the inspection result your software must produce.

If the system mainly identifies presence, reads information or classifies defects, a standard high-quality Machine Vision Lens may be entirely appropriate.

If the system calculates physical dimensions, positions or coordinate differences, geometric performance deserves much more attention.

Next define the tolerance.

A millimetre-level positioning application has very different requirements from a measurement system working at a few hundredths of a millimetre.

Determine whether the whole image is used.

If all measurements occur near the centre, the optical requirement can differ from an application where objects move anywhere across a large sensor.

Check camera resolution and sensor format.

A large high-resolution sensor uses more of the image circle and can make edge behaviour more relevant.

Select focal length from field of view and working distance.

Then evaluate distortion and perform system calibration.

This sequence avoids choosing a low distortion lens simply because the phrase sounds desirable.

Where Kyptec Automation® Fits into Measurement and Positioning Lens Selection

Kyptec Automation® provides Machine Vision Lenses across multiple sensor formats, focal lengths and resolution classes for industrial automation and inspection applications.

For compatible 1 inch, 10 MP systems, Kyptec Automation® KL-1216 provides 25 mm focal length and Kyptec Automation® KL-1218 provides 35 mm.

For compatible 2/3 inch systems requiring a longer working-distance configuration, Kyptec Automation® KL-1232 provides a 50 mm, 10 MP option.

For demanding larger-format high-resolution systems, Kyptec Automation® KL-1240 provides 25 mm and Kyptec Automation® KL-1244 provides 50 mm within the 25 MP class.

These examples are useful because measurement applications still need the correct basic imaging geometry before distortion can be evaluated.

A lens with excellent geometric behaviour is not useful if it produces the wrong field of view or fails to cover the camera sensor.

The advantage of selecting from the Kyptec Automation® Machine Vision Lens category is that focal length, sensor format and optical resolution can be matched first, after which the complete configuration can be validated for the required measurement accuracy.

Final Answer: Low Distortion or Standard Machine Vision Lens?

Choose a standard Machine Vision Lens when the inspection mainly needs image detail, recognition or presence information and small geometric deviations do not materially affect the pass or fail result.

Give low distortion much higher priority when the camera performs dimensional measurement, precision gauging, coordinate calculation, robotic positioning or other tasks where the numerical location of an image feature matters.

Do not assume that low distortion eliminates the need for calibration.

Do not assume that calibration makes optical distortion irrelevant.

The strongest measurement system uses appropriate optics, controlled camera geometry and accurate calibration together.

Also remember that distortion is only one part of the lens specification.

The lens still needs the correct focal length, field of view, working distance, image format, optical resolution, aperture range and mechanical compatibility.

For buyers, OEMs and machine vision system integrators, the best decision is therefore not “low distortion is always better.”

The better decision is:

How much geometric error can this application tolerate, and how much of that error budget can reasonably be assigned to the lens?

Once that question is answered, choosing between a standard and low distortion Machine Vision Lens becomes an engineering decision rather than a marketing specification.