SWIR Camera Lens for Wood, Timber and Engineered Board Inspection: Moisture, Resin, Adhesive and Material Variation Detection

Wood, timber and engineered board manufacturing present a difficult machine-vision challenge because many important quality differences are chemical or internal rather than purely visual. Two boards can look similar under visible light while having different moisture levels, resin distribution, adhesive content, fiber composition, species mix or surface treatment. Wood-based materials are also naturally heterogeneous: grain direction, knots, earlywood and latewood regions, density, porosity and moisture can all change optical response across a single board. For manufacturers producing sawn timber, veneer, plywood, laminated timber, particleboard, fiberboard and other engineered panels, this variability creates a strong case for SWIR imaging for wood inspection, because wavelength-dependent short-wave infrared response can provide information about material state that conventional colour imaging cannot reliably reveal.

Research into spectral imaging of wood has demonstrated that near-infrared and short-wave infrared measurements can be used to predict moisture content, analyze resin distribution, classify raw material variation and support quality assessment in wood-based products. Hyperspectral imaging studies have successfully predicted wood moisture content from spectral data, while chemical imaging has been used to quantify resin distribution inside treated wood and to show process-related resin migration. These findings are especially relevant for industrial inspection because they demonstrate that wood's infrared response contains information related not only to visual texture but also to moisture and chemical composition.

A dedicated 900–1700 nm SWIR Camera Lens provides the optical link needed to capture this type of information with an appropriate SWIR camera. The current Kyptec Automation® SWIR Camera Lens collection contains five focal-length options—8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm—allowing machine builders to configure broad board inspection, conveyor-based timber sorting, localized adhesive inspection and longer-working-distance systems. The live collection currently confirms exactly these five products. Representative models are designed around 900–1700 nm operation, 2 MP resolution, 2/3-inch sensor format, F1.4 aperture and C-Mount, providing a focused optical platform for material-sensitive SWIR inspection.

Why Wood Is Well Suited to Spectral Inspection

Wood contains water, cellulose, hemicellulose, lignin, extractives and other chemical constituents whose infrared absorption and scattering behaviour varies with wavelength. This means that two locations with similar visible colour can respond differently in short-wave infrared if their moisture, composition, density or treatment differs. Spectral imaging is therefore particularly useful when manufacturers need to go beyond ordinary surface inspection and measure variations that are linked to material state rather than appearance alone.

The natural heterogeneity of wood makes this both valuable and challenging. A good SWIR system should not assume that every intensity difference represents a defect. Grain orientation, species, surface roughness and machining condition can also change reflectance. Industrial classification therefore requires representative training and calibration samples covering normal wood variability so that genuine defects or process deviations can be distinguished from expected biological variation.

Moisture Detection Is One of the Strongest SWIR Applications in Wood Processing

Moisture content affects drying, machining, dimensional stability, adhesive performance and final product quality. Studies using hyperspectral and near-infrared imaging have demonstrated strong potential for predicting wood moisture, including work showing high predictive accuracy across multiple moisture states in wood samples. This makes moisture-sensitive SWIR inspection particularly relevant after kiln drying, before adhesive application, during board production and before final quality grading.

A production imaging system can provide more than a single average moisture value. Because each image contains spatial information, the system can reveal moisture gradients, wet edges, localized high-moisture zones and non-uniform drying across the board surface. This is especially useful for large panels where an average measurement could hide a small but important wet region.

Moisture Mapping Can Reveal Drying Non-Uniformity

Drying processes do not always remove moisture uniformly. Differences in airflow, board thickness, density, stacking position and local material structure can create regions that dry at different rates. SWIR imaging can potentially map these variations across the board instead of relying on one or two spot measurements.

For production control, the objective should not simply be to classify the board as “wet” or “dry.” A stronger system can determine whether moisture variation across the board exceeds an acceptable spatial limit. This makes SWIR imaging useful for process optimization as well as final inspection, because manufacturers can identify patterns linked to dryer zones, board positions or operating conditions.

Wood Species and Raw-Material Variation Can Influence Spectral Classification

Different wood species have different chemical composition, density, extractive content and cellular structure. These variations can influence their infrared spectral response. In engineered-board production, mixtures of chips or fibers from different raw materials can therefore change the optical characteristics of the feedstock even before resin is applied.

Industrial hyperspectral systems have been used to quantify wood-chip composition and moisture in board-manufacturing processes, supporting process adjustment before defibering, gluing and pressing. For a SWIR imaging system, this means material classification can potentially assist raw-material consistency monitoring where the spectral differences between chip types are sufficiently repeatable.

Resin Distribution Is an Important Engineered-Wood Quality Variable

Resin and impregnation chemicals are used in many engineered or treated wood products, and non-uniform distribution can affect strength, durability, dimensional stability and downstream processing. Chemical imaging research has shown that hyperspectral near-infrared imaging can quantify resin distribution in treated wood and reveal process-dependent migration toward board surfaces.

This creates a useful inspection concept for SWIR machine vision: if the resin produces a measurable spectral response different from untreated wood, an imaging system can potentially map where resin concentration is relatively high or low. Rather than checking only whether resin was applied, manufacturers can evaluate distribution uniformity across the relevant surface or region.

Resin-Rich and Resin-Poor Zones Can Affect Final Panel Quality

A resin-poor region may not develop the same bonding performance as the surrounding material, while excessive resin can increase cost and potentially change pressing behaviour or surface properties. The exact relationship depends on the board process and adhesive chemistry, but the production objective is normally consistent application within the specified range.

SWIR inspection can be valuable where spectral contrast between the wood substrate and resin system is strong enough to reveal distribution patterns before pressing or at another accessible production stage. The important point is that this should be validated on the actual formulation because different resin systems can produce different spectral signatures.

Adhesive Quality Control Requires More Than Detecting a Visible Glue Line

In laminated timber, plywood and other bonded wood products, the adhesive may be difficult to distinguish visually, especially after spreading or partial curing. Near-infrared methods have been investigated for quality assurance in glue-laminated timber and have shown capability for predicting moisture, identifying defects and even assessing delamination-related quality variables. Near-infrared spectroscopy has also been used to characterize the chemical composition of resin systems used in wood-based panel manufacturing.

For SWIR imaging, the practical opportunity is to detect adhesive presence, distribution variation or material inconsistency when those differences create sufficient spectral contrast within the available wavelength region. The system should not assume that every adhesive is equally visible. The exact adhesive, wood species, spread rate and cure condition should be tested together.

Moisture and Adhesive Behaviour Are Closely Linked in Wood Manufacturing

Wood moisture can influence adhesive curing and bond formation. Research has shown that moisture content affects curing behaviour in adhesive-wood mixtures, reinforcing the importance of controlling both the substrate condition and adhesive process. This creates a valuable production relationship: an adhesive problem may not originate from the adhesive alone but from moisture variation in the wood entering the bonding process.

A SWIR system positioned upstream can therefore contribute to bond-quality assurance by monitoring wood moisture before glue application, while another inspection stage can evaluate whether adhesive distribution itself is sufficiently uniform. These are distinct measurements but can be connected within one quality-control strategy.

Engineered Board Production Can Benefit From Raw-Material Classification

Particleboard and fiberboard production depend on relatively consistent raw-material properties before pressing. Variation in species, chip size distribution, moisture and recycled material can affect process settings and final board quality. Spectral imaging can provide spatial and compositional information about the material flow before it becomes compressed into a finished panel.

This is particularly useful where recycled feedstock is involved because residual adhesives, plastics or other foreign material may be present. Research on recycled particleboard feedstock shows that adhesive residues can influence board properties and bonding behaviour. A SWIR classification system can therefore be evaluated as part of a broader incoming-material verification process where different constituents produce separable spectral signatures.

Foreign Material Detection Can Protect Board Manufacturing Processes

Plastic fragments, rubber, adhesive residues, bark, foreign fibers and other contaminants can enter chip or fiber streams. Industrial spectral systems have demonstrated the ability to identify plastics, gums and other foreign materials within wood-board production streams.

The value of SWIR in this context is that a foreign material does not need to have a different visible colour from the wood. If its chemical composition produces a different infrared response, the system may detect it based on spectral contrast. This makes SWIR especially useful for contaminants that conventional colour sorting may overlook.

Veneer Inspection Can Use SWIR to Evaluate Material Uniformity

Veneer sheets are thin enough that moisture, resin, adhesive and underlying support conditions can influence their SWIR response. During plywood or laminated-board production, this creates opportunities for detecting localized material differences before bonding.

Because veneer is thin, background selection becomes important. If the veneer transmits part of the SWIR illumination, the conveyor or support underneath can contribute to measured intensity. The support should therefore be spectrally stable and validated together with the veneer so that background variation is not mistaken for product variation.

Plywood Glue-Line Inspection Requires the Correct Production Stage

Once a plywood panel has been fully pressed, internal glue lines may become difficult to access optically. SWIR inspection should therefore be positioned at the stage where the relevant adhesive or veneer interface remains visible or sufficiently transmissive to the selected wavelength.

This highlights a broader design principle: the best SWIR station is not always the final inspection station. For adhesive spread or resin distribution, an earlier in-process measurement can provide much stronger optical access than post-press inspection.

MDF and Fiberboard Inspection Requires Material-Specific Calibration

Medium-density fiberboard and related engineered products contain fibers, resin, waxes and other additives rather than the simple structure of solid timber. Their SWIR signal therefore reflects the combined response of several constituents.

A calibration developed for solid wood should not automatically be transferred to engineered board. The correct approach is to create representative samples spanning production variation in moisture, density and formulation. The imaging system can then determine whether selected wavelength features remain sufficiently stable for useful classification.

Particleboard Surface and Core Conditions Can Differ

Particleboard is inherently layered and heterogeneous. Surface particles, core particles, density and resin distribution can vary through thickness. A reflection-mode SWIR image primarily measures the optical information accessible from the viewed surface and near-surface region, so it should not automatically be interpreted as a complete measurement of the board core.

If internal condition is the target, wavelength penetration and board thickness should be investigated experimentally. The inspection claim should always match the depth from which useful SWIR information can actually return to the camera.

Surface Roughness Can Change SWIR Intensity

Planed timber, rough-sawn timber and sanded board surfaces scatter infrared illumination differently. A rougher surface can redistribute light over more angles, while a smooth surface may create more directional reflection. This means the same material can produce different grayscale values purely because of surface finish.

Material-classification models should therefore include the expected roughness range. Where possible, the machine should inspect at a consistent process stage so surface condition remains controlled. Relying on one absolute intensity threshold across widely different surface finishes can produce unnecessary false classifications.

Grain Direction Can Influence Reflectance

Wood is anisotropic, meaning its structure changes with direction. Longitudinal grain, radial surfaces and tangential surfaces can scatter light differently. Boards entering a system with different grain orientation may therefore create intensity variation unrelated to moisture or resin.

The system should be validated using the full range of normal grain patterns rather than a small group of visually uniform samples. A robust classifier learns or normalizes these natural variations while remaining sensitive to the actual defect variable.

Knots Should Usually Be Treated as a Distinct Material Region

Knots differ from surrounding clear wood in density, grain orientation, resin or extractive content and physical structure. Their SWIR response can therefore differ strongly from nearby timber even when they are not considered defective for the application.

A classification system should decide explicitly whether knots are acceptable, restricted or reject conditions. If they are acceptable, they should be included in training so the algorithm does not mistake natural knot contrast for moisture or adhesive variation.

Reflection Geometry Is Often Practical for Timber Conveyors

For solid timber and board surfaces, reflection-mode SWIR imaging is usually attractive because the illumination and camera can remain on the same side of the production line. The source illuminates the surface, the wood absorbs and scatters selected wavelengths, and the returned radiation is imaged by the SWIR Camera Lens.

This architecture is practical for continuous conveyors, but the illumination angle should remain stable across the field. Changes in board height or tilt can alter returned intensity, so mechanical guidance and reference normalization can improve repeatability.

Transmission Geometry Can Be Valuable for Thin Wood Products

Thin veneer or selected board layers may permit enough SWIR transmission for backlit inspection. In such cases, differences in moisture, adhesive or material thickness can change how much radiation passes through the product.

Transmission should be evaluated only where the material allows sufficient signal at the required wavelength. Thick timber will generally attenuate too strongly for conventional transmission imaging, making reflection the more realistic production geometry.

1450 nm Can Be Useful for Wood Moisture, but It Is Not Automatically the Only Choice

Water exhibits strong absorption around 1450 nm, making this region highly relevant to moisture-sensitive SWIR imaging. However, wood itself contains multiple absorbing and scattering constituents, so the optimum production wavelength may not sit exactly at the strongest water band.

If highly moist or thick timber becomes too dark at 1450 nm, a nearby wavelength with weaker absorption may provide better quantitative headroom. The correct band is the one that separates acceptable and excessive moisture most reliably across the required production range.

Multi-Wavelength Imaging Can Separate Moisture From Surface Variation

A single SWIR image may change because of moisture, illumination level, surface roughness or board height. Using a moisture-sensitive wavelength together with a less moisture-sensitive reference wavelength can reduce some of these common variations.

Ratios or normalized differences can therefore provide a more stable moisture indicator than raw grayscale intensity, particularly when wood surfaces vary naturally. The method should still be calibrated separately for different species or product families where their baseline spectral response differs substantially.

Kyptec Automation® KL-1408 for Wide Timber and Board Inspection

The Kyptec Automation® KL-1408 8.5 mm SWIR Camera Lens can be evaluated where a broad board, conveyor region or multiple wood pieces need to fit inside one image. The live SWIR collection confirms 8.5 mm as the widest focal-length option among the current five-product range.

A wider FOV is useful for moisture mapping across larger board areas, but the smallest resin, adhesive or material feature must still occupy enough pixels for reliable detection. Field width should therefore be calculated from the real defect size rather than from board width alone.

Kyptec Automation® KL-1410 for Balanced Wood Inspection Geometry

The Kyptec Automation® KL-1410 12.5 mm SWIR Camera Lens can provide a useful balance between coverage and spatial sampling for timber and engineered-board applications. It is suitable to evaluate where a machine needs substantial field width without allocating too few pixels to localized moisture or adhesive variation.

This intermediate geometry can be particularly practical for conveyor inspection where the system must monitor both the material region and enough surrounding area for reliable board positioning.

Kyptec Automation® KL-1412 for Localized Resin and Adhesive Inspection

The Kyptec Automation® KL-1412 25 mm SWIR Camera Lens can be considered when the inspection focuses on a smaller glue line, veneer section, treated region or material feature. A tighter field allocates more pixels to the region of interest and can improve the ability to map small variations.

The lens does not increase the chemical contrast itself; it improves the spatial representation of the contrast that already exists at the selected SWIR wavelength.

Longer Focal Lengths Can Support Inspection From Greater Stand-Off

The Kyptec Automation® KL-1414 35 mm SWIR Camera Lens and Kyptec Automation® KL-1416 50 mm SWIR Camera Lens can be useful where the camera must remain farther from sawdust, dust extraction, moving boards or other harsh process areas while observing a relatively controlled inspection region. The current Kyptec Automation® collection confirms both focal lengths as part of the same five-lens SWIR portfolio.

Greater working distance can improve mechanical protection but may require more illumination and careful alignment. The final focal length should therefore be selected jointly from FOV, stand-off and minimum detectable feature.

F1.4 Can Support High-Speed Conveyor Imaging

Wood and board production lines often move continuously, limiting exposure time. Narrowband SWIR illumination and strongly absorbing moisture regions can further reduce signal. The F1.4 capability available in representative Kyptec Automation® SWIR Camera Lenses provides useful light-gathering flexibility where short exposures are required.

The aperture should still be balanced against depth of field. Timber thickness and board height can vary, so operating fully open may reduce focus tolerance if the process plane is not sufficiently controlled.

Why Kyptec Automation® Is a Strong Choice for Wood and Engineered-Board SWIR Inspection

The Kyptec Automation® SWIR Camera Lens collection provides a focused range of five focal lengths—8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm—giving wood-processing OEMs flexibility to adapt the image geometry to full-board inspection, conveyor sorting, localized adhesive analysis or longer stand-off. The live collection confirms all five products.

This is valuable because wood applications differ greatly in scale. A large timber board may require broad coverage, while a glue line or localized resin distribution region may need tighter sampling. Kyptec Automation® allows the spectral problem and geometric problem to be solved independently but within the same dedicated SWIR Camera Lens category, making the portfolio a strong optical foundation for industrial wood-material inspection.

Frequently Asked Questions About SWIR Camera Lenses for Wood, Timber and Engineered Board Inspection

1. Can SWIR imaging measure moisture in wood?

Yes, SWIR and near-infrared spectral methods can be highly sensitive to moisture because water produces characteristic infrared absorption. Research using hyperspectral imaging has successfully predicted wood moisture content across controlled drying stages. Production accuracy still depends on wood species, thickness, surface condition and calibration, so a machine should be developed using representative timber samples rather than one universal moisture threshold.

2. Can SWIR detect uneven moisture across a timber board?

Yes. Because imaging provides spatial information, a SWIR system can reveal regions that differ in moisture-sensitive response across the board. This can help detect wet edges, localized high-moisture zones or uneven drying that an average point measurement could miss. The system must correct for illumination and field-position variation so spatial brightness differences are not confused with real moisture gradients.

3. Can SWIR distinguish different wood species?

Potentially, because species differ in chemical composition, density and structure, which can affect their spectral response. Industrial spectral systems have been used to classify different wood-chip types in board production. Whether a particular pair of species can be separated reliably should be tested using samples covering normal variability such as grain, age and moisture.

4. Can SWIR imaging detect resin distribution in treated wood?

Research has demonstrated that hyperspectral near-infrared chemical imaging can quantify resin distribution in impregnated wood and reveal process-driven resin migration. This supports the feasibility of using spectral imaging to investigate resin-rich and resin-poor regions where the resin produces sufficient contrast against the wood substrate.

5. Can SWIR inspect adhesive application in plywood or laminated timber?

It can be evaluated where the adhesive has a measurable spectral response different from the wood surface. The best inspection stage is usually before the glue line becomes inaccessible inside the finished panel. Near-infrared techniques have been investigated for quality assurance in laminated timber and for adhesive-related material analysis, supporting the broader feasibility of spectral approaches.

6. Can SWIR detect a missing glue area?

Potentially, if the adhesive and bare wood produce enough contrast at the selected wavelength. A missing adhesive region would then appear spectrally closer to untreated wood than to correctly coated material. The minimum detectable area depends on image resolution, adhesive thickness, wood surface variation and the strength of the spectral difference.

7. Does wood grain affect SWIR inspection?

Yes. Grain orientation changes surface geometry and internal structure, affecting how infrared radiation scatters and returns to the camera. A robust classifier should therefore include normal grain variation during calibration. Otherwise, strong grain differences can be incorrectly interpreted as moisture or composition changes.

8. Can knots create false detections in SWIR timber inspection?

Yes, because knots can have different density, grain orientation and chemical composition from clear wood. Their SWIR response may differ significantly even when they are acceptable. Knots should therefore be represented explicitly during training and classified according to the real product specification rather than treated as unexpected anomalies.

9. Can SWIR inspect MDF moisture content?

It can be evaluated because engineered fiberboard contains water-sensitive and chemically distinct constituents, but the calibration should be developed specifically for the MDF formulation. Fiber density, resin content and additives may influence spectral response. A model developed for solid timber should not automatically be applied to fiberboard.

10. Can SWIR inspect particleboard raw materials before pressing?

Yes, and this can be especially valuable because moisture, wood-chip composition and foreign material can influence the downstream board process. Industrial spectral imaging has been demonstrated for quantifying wood-chip types, moisture and foreign elements before later board-manufacturing stages. This makes raw-material inspection an attractive point for SWIR integration.

11. Can SWIR detect plastic contamination in wood chips?

Potentially, if the polymer's SWIR response differs sufficiently from the wood chips. Spectral inspection has been used to identify plastics and other foreign materials in wood-board production streams. This is particularly useful where contaminant colour is similar to the wood and therefore difficult to detect with conventional visible imaging.

12. Does surface roughness affect SWIR moisture measurements on timber?

Yes. Roughness changes scattering and can change the amount of radiation returning to the camera independently of moisture. If rough-sawn and planed boards are inspected with the same threshold, classification accuracy may decline. Production calibration should include the expected surface-finish range or inspect after a standardized machining stage.

13. When should I use the Kyptec Automation® KL-1408 for timber inspection?

The Kyptec Automation® KL-1408 8.5 mm SWIR Camera Lens can be evaluated when a broad timber board, conveyor region or multiple pieces need to fit within one image. Its wider FOV is well suited to large-area moisture mapping, provided the smallest defect or material variation still occupies enough pixels. It forms part of the current five-model Kyptec Automation® SWIR range.

14. When is the Kyptec Automation® KL-1412 useful for resin or glue inspection?

The Kyptec Automation® KL-1412 25 mm SWIR Camera Lens can be useful when the inspection is concentrated on a smaller treated area, glue line or veneer region. Tighter framing allocates more sensor pixels to the feature, improving spatial measurement when the resin or adhesive contrast has already been established spectrally.

15. Are 35 mm and 50 mm SWIR Camera Lenses useful in dusty wood-processing machines?

They can be useful where additional stand-off allows the camera to remain farther from sawdust, moving material or difficult machine areas. The Kyptec Automation® KL-1414 35 mm SWIR Camera Lens and Kyptec Automation® KL-1416 50 mm SWIR Camera Lens provide narrower-field options within the current portfolio. The final configuration should still maintain enough illumination and spatial resolution at the chosen working distance.

16. Can one SWIR calibration work for pine, hardwood and engineered board?

Usually not without validation. Different species and board formulations have different baseline spectra, density, moisture response and chemical composition. A calibration may be transferable only if testing shows that those differences remain within the model's acceptable range. Product-family-specific recipes are often more reliable than assuming one universal wood classifier.

17. Can SWIR detect adhesive cure quality directly?

SWIR may detect spectral changes associated with adhesive composition, moisture or curing state, but the relationship should be established experimentally for the specific adhesive system. Infrared spectroscopy has been used to study chemical changes in wood adhesives, demonstrating that cure processes can alter measurable spectral characteristics. A production imaging system should be calibrated against independently verified cure conditions before making pass/fail decisions.

18. What should be tested before buying a SWIR Camera Lens for wood inspection?

The feasibility study should include wood species, moisture range, surface roughness, grain variation, knots, resin or adhesive formulations, board thickness, line speed, required FOV and minimum defect size. The relevant wavelengths should be identified first, after which focal length can be selected from the Kyptec Automation® SWIR Camera Lens collection according to working distance and spatial coverage.

19. What is the biggest mistake when designing a SWIR wood inspection system?

A major mistake is treating all brightness variation as chemical variation. Wood naturally changes in grain, density, roughness and species, and each factor can affect the SWIR signal. A strong system establishes the expected natural variation first, then determines whether moisture, resin, adhesive or contamination still produces a sufficiently distinct spectral signature. Optical control and representative calibration are therefore essential.

20. Why is Kyptec Automation® a strong choice for wood and engineered-board SWIR inspection?

Kyptec Automation® provides a dedicated SWIR Camera Lens collection spanning 8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm, which allows OEMs to match the optics to full-board imaging, conveyor inspection, localized resin or adhesive analysis and longer-working-distance applications. The live collection currently confirms all five focal lengths. This flexibility is valuable because wood inspection combines large-area material mapping with small localized quality features. Kyptec Automation® therefore provides a strong optical platform for developing 900–1700 nm inspection systems around the real FOV, stand-off and spatial-resolution requirements of the wood process.

Conclusion

SWIR Camera Lens technology offers a powerful way to move wood and engineered-board inspection beyond visible appearance and toward material-sensitive quality control. Moisture content, resin distribution, adhesive variation, raw-material composition and selected foreign materials can all create wavelength-dependent infrared responses that are difficult or impossible to interpret from colour images alone. Research in wood spectroscopy and spectral imaging has already demonstrated strong potential for moisture prediction, resin mapping, adhesive-related quality assessment and raw-material classification.

For solid timber, one of the most valuable opportunities is moisture mapping. Instead of measuring one isolated point, a SWIR imaging system can evaluate moisture-sensitive variation across a wider board region, helping manufacturers identify uneven drying, localized wet areas and position-dependent process variation. For engineered products, the application becomes broader: resin distribution, adhesive presence, chip composition and foreign-material contamination can potentially be analyzed when they provide sufficiently distinct spectral signatures. The strongest system does not assume that one wavelength or threshold will work for every wood product; it validates the exact species, formulation, moisture range and production condition.

Optical geometry is equally important. Large boards and conveyors require broad FOV, while glue lines and localized resin features require higher spatial sampling. Dusty or mechanically restricted processes may benefit from greater working distance. The current Kyptec Automation® SWIR Camera Lens collection provides 8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm focal lengths, giving OEM machine builders a practical way to match the field of view to each inspection stage while remaining within one dedicated SWIR category.

For industrial buyers and system integrators, the central principle is to define the wood-quality variable first, identify the wavelength where that variable produces stable contrast, then select the SWIR Camera Lens according to FOV, working distance and minimum feature size. Moisture inspection, resin mapping, adhesive verification and material classification are different problems and should be calibrated separately. When spectral material behaviour and optical geometry are engineered together, Kyptec Automation® SWIR Camera Lenses provide a strong foundation for reliable industrial inspection of wood, timber, veneer, plywood, particleboard, fiberboard and other engineered wood products.