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Hem / Case studies / Apple bruises: NIR vs SWIR
Application study · Food and agriculture

Seeing bruises under the skin: NIR vs SWIR on apples

Two supplied images of the same apple compare 940 nm near-infrared and 1550 nm short-wave infrared. The 1550 nm capture shows stronger dark patches at the marked bruises, illustrating why wavelength choice matters.

Match the wavelength, sensor and optics as one system.

  • NIR940 nm
  • SWIR1550 nm
  • KameraInGaAs, 900–1700 nm
  • ResultBruises dark and wide at 1550 nm
3D view of the inspection set-up: camera, lens, light and partDrag to rotate · scroll to zoom
3D illustration · real CAD where available
Walk through this setup 5 guided stops
From component to inspection

Understand each choice.

Choose a stop to frame the part in 3D and see why it belongs in this setup. The component notes and links remain available if 3D cannot load.

Camera and available lens CAD are published models. Lens and light envelopes use printed dimensions. The linked station uses its published base size and column height; carriage, brackets, fittings, parts and spacing are illustrative. Confirm load, travel, fasteners and clearances before ordering. Light paths explain the arrangement and do not simulate optical performance. The 400 mm lens-to-part spacing respects the printed 0.38 m minimum object distance. The drawn 90 × 72 mm viewing region is illustrative and needs confirmation by focusing and calibration; it is not a measured source field.

From the demo to your test bench

Build around the parts you can buy.

Explore each component, check its specifications and compare alternatives. The proposed quote includes the linked test station; its catalog listing includes two lighting holders.

Mount the optics with intent

The station is an optical test bench, with its two lighting holders included in the catalog listing. The 3D column and base follow the published height and footprint. Carriages, clamps and part supports are schematic: confirm camera screw pattern, lens support, light fasteners, permissible load and actual travel before ordering.

Configure the mounting station →

Complete the electrical system

Select a controller against the exact light voltage, drive mode and power, then confirm camera data/power/I/O cables and a suitable PC. These are not silently added to the proposed optical kit.

Lighting application-lab image sheet

Evidence you can inspect

Visible in the images

The annotated 1550 nm image shows two dark regions more distinctly than the 940 nm image.

What the source reports

The sheet labels the wavelengths as 940 nm and 1550 nm; it supplies no sorting accuracy or bruise-depth data.

How to use this evidence

One illustrated sample. Confirm contrast across your fruit varieties, ripeness and damage ages.

What the camera saw

Cropped from the source test sheet; original test annotations are retained. Captures are not generated or enhanced. Drag the comparison slider or use the image buttons.

NIR 940 nm: one soft area, low contrast (marked by the tester).SWIR 1550 nm: two dark bruises with clear borders (marked by the tester).NIR 940 nmSWIR 1550 nm
NIR 940 nm: NIR 940 nm: one soft area, low contrast (marked by the tester).
SWIR 1550 nm: SWIR 1550 nm: two dark bruises with clear borders (marked by the tester).
The part: an apple that looks undamaged in colour.
The part: an apple that looks undamaged in colour.

The challenge

The colour photograph shows little obvious surface damage. The inspection problem is to find damage that has weak visible contrast.

Near-infrared at 940 nm goes a little deeper and shows one soft area, but the contrast is low and the second bruise is missed.

How it was solved

Changing wavelength changes the relative absorption and scattering of light in the fruit. This application compares 940 nm with 1550 nm; tissue and moisture differences can affect that contrast.

The test imaged the same apple at 940 nm and at 1550 nm. At 1550 nm both bruises show as dark patches with clear borders, including one at the top that the 940 nm image misses.

Why it works

  1. 1

    The supplied 1550 nm capture shows stronger bruise contrast on this apple. Cultivar, maturity and time since damage need separate validation.

  2. 2

    The proposed SWIR camera and lens cover the required band. A standard visible-only camera cannot be assumed to work at 1550 nm.

  3. 3

    The purple light paths in the 3D scene are a visual convention for invisible infrared; they do not depict a visible purple source or measured penetration.

From image contrast to a production decision

What to validate on your part

A useful sample image is the starting point. These are the checks that turn the concept into a defensible inspection.

  1. 01

    Cover real variation

    Test varieties, ripeness, surface moisture and different times after damage.

  2. 02

    Match the complete spectral path

    Verify the light wavelength, lens transmission, filters and sensor response together.

  3. 03

    Check movement

    Set exposure and trigger timing using fruit moving at the intended conveyor speed.

Explore your inspection requirements

How many pixels cover your feature?

Compare feature coverage, camera pixel requirements and exposure using your own planning inputs. These are calculated planning values, not inspection results or an accuracy specification.

Editable planning scenario. Adjust these example inputs for your application; they are separate from the source test and 3D setup. Motion allowance and target coverage are starting points to validate, not acceptance limits. Pixel count starts from the proposed camera's catalog resolution.

Object sampling0.07812 mm/px
Pixels across feature6.4 px
Horizontal pixels for target1000 px
Motion during exposure0.128 px
Exposure ceiling from motion390.6 µs
Formulas and assumptions

The field, feature, speed and exposure start with neutral example values. They are not taken from the source test or the 3D illustration. Allowed motion starts at an editable 0.5-pixel example; it is not a recommended acceptance limit. Target coverage starts at an editable 5-pixel example; it is not a recommended detection or measurement threshold. The horizontal pixel count starts from the catalog Resolution row for MV-CI013-GS-NN. Use the effective width after cropping, binning or decimation if those modes are enabled.

  • Object sampling (mm/px) = field width (mm) / horizontal pixels.
  • Pixels across feature = feature width (mm) / object sampling (mm/px).
  • Horizontal pixels for target = field width (mm) × target pixels across feature / feature width (mm), rounded up to a whole pixel.
  • Motion (px) = speed (mm/s) × exposure (µs) / 1,000,000 / object sampling (mm/px).
  • Exposure for allowed motion (µs) = allowed motion (px) × object sampling (mm/px) / speed (mm/s) × 1,000,000.

The exposure result is the maximum duration from this motion allowance alone. At zero speed, motion sets no exposure limit; the camera, lighting, saturation and other constraints still apply. A shorter exposure does not itself guarantee a reliable inspection.

Field width and feature width refer to the same object plane. The motion calculation assumes uniform linear motion parallel to the field-width direction and a single exposure. It does not model perspective, vibration, rolling-shutter distortion, diffraction, defocus or optical distortion. A strobe may change the effective exposure.

The target result is a horizontal sampling requirement, not a camera recommendation or a change to the selected camera. It uses the effective image width after cropping, binning or decimation and does not determine the vertical resolution or sensor size. Pixel coverage alone does not establish detectability or measurement accuracy. Validate contrast, lens performance, working distance, illumination, calibration, camera exposure limits and the inspection algorithm on representative parts. Changing field width does not change the 3D model or certify that the proposed lens can achieve that field.

The set-up and the parts

LjusSWIR LED light, 1550 nm (and 940 nm for comparison)
KameraInGaAs SWIR area scan
ObjektivSWIR-corrected, 900–1700 nm
Mounting (proposed)LS-BT-XZ-G-8-6045 · camera test station with glass tray and two lighting holders
Proposed lens focusing limitPrinted minimum object distance 0.38 m; illustrated lens-to-part spacing 400 mm
Illustrative viewing region90 × 72 mm; not the source field or a verified lens field specification
Configure the standard components

Custom configuration requirements stay attached to this quote. The configurator starts with the standard parts; confirm the custom lights with your quote.

"Tested" identifies the part named in the source. "Our pick" is a proposed alternative or supporting part. The quote includes only cards marked "In proposed setup", with the quantities shown; other test arrangements are separate. Confirm colour, optics, controllers, power supplies, cables and mounting before ordering.

About this case study: the photos and camera images come from the application laboratory of the maker of the lighting and optics we sell, imaged on the parts shown; your results depend on your part, camera and set-up. This is an application-lab study, not a LumaSpec customer deployment. Source figures are reported results; proposed components require a fresh trial. The 3D scene illustrates the arrangement and does not simulate imaging performance.

More case studies

Start with your inspection requirement

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Tell us the part size, smallest defect or tolerance, available working distance, material and line speed. Include what a good part and a reject look like.

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