Imaging Experiment Report on Bread Freshness Inspection Using SWIR1503B10G SWIR Camera

Author:Attostek    ·    Release Date :06/13/2026    ·    Category :Industrial Inspection

Imaging Experiment Report on Bread Freshness Inspection Using SWIR1503B10G Short-Wave Infrared Camera
Testing Period: May 2026

1. Test Purpose

To verify the capability of Attostek’s SWIR1503B10G short-wave infrared (SWIR) camera to judge bread freshness by measuring bread moisture content, and compare its imaging performance with a visible-light camera.

2. Application Background & Detection Principles

2.1 Application Background

Bread is a convenient and staple food for breakfast and afternoon tea, mainly made from water, wheat flour, sugar, eggs, yeast, with cream, chocolate, dairy and other additives commonly included in most varieties. Bread is prone to dehydration, and its freshness directly determines mouthfeel. As consumers pursue higher quality of life and food safety standards, there is growing demand for fresher, healthier bread products.

2.2 Detection Principle

Traditional freshness assessment relies on production date labels or manual tactile pressing, which cannot deliver objective quantitative results. Bread staleness is primarily caused by moisture loss: fresh bread retains high moisture content, while prolonged storage leads to gradual water evaporation and a dry, hard texture. Water molecules strongly absorb infrared light near the 1450 nm wavelength. Leveraging this characteristic, SWIR imaging enables non-contact mapping of moisture distribution inside bread:

  • Fresh bread with high moisture absorbs more infrared light and appears dark in captured images;
  • Stale, dehydrated bread absorbs less infrared light and reflects more, appearing bright.

Differences in grayscale values allow fast, intuitive evaluation of bread freshness. Additional infrared illumination and infrared bandpass filters can be deployed to amplify the contrast in reflected light intensity between fresh and stale bread captured by the camera.

2.3 Camera Performance Requirements

  • High Signal-to-Noise Ratio (SNR)
  • High Quantum Efficiency (QE)

Specifications of the SWIR051AU camera referenced in this report:

  • Maximum SNR: 62.98 dB
  • Quantum efficiency at 1300 nm: approx. 75%

3. Test Equipment & Parameters

Equipment / ComponentModel / Specification
Short-Wave Infrared CameraAttostek SWIR1503B10G
Visible-Light CameraAttostek VIS028CU3.2-NC
Light Source1300 nm infrared light source
Optical Filter1300 nm infrared bandpass filter
Test SamplesFresh bread, bread stored for 24 hours (stale dry bread)
Ambient ConditionsIndoor environment, no extra ambient lighting apart from experimental fill light; temperature stabilized at 25°C

4. Test Procedures

  1. Place fresh bread and 24-hour stale bread side by side; fix the SWIR1503B10G camera and adjust sample positions to center the bread within the lens field of view.
  2. Manually adjust camera focus and aperture to achieve clear imaging.
  3. Set appropriate exposure time (manual or auto exposure mode).
  4. Capture images with the SWIR1503B10G camera under four separate conditions:
    • No filter or auxiliary light source
    • 1300 nm infrared fill light only
    • 1300 nm infrared filter only
    • Combined 1300 nm filter + 1300 nm fill light
  5. Capture comparative reference images at the identical position using the VIS028CU3.2-NC visible-light camera.

5. Test Results

5.1 Visual Image Observation

  1. Visible-light camera (VIS028CU3.2-NC):
    Fresh bread shows standard golden-yellow surface with normal appearance. After 24 hours of storage, the bread crust retains its original color with negligible shrinkage, making visual differentiation of freshness nearly impossible.
  2. SWIR1503B10G direct shooting (no filter/light):
    Moisture-rich fresh bread forms dark image regions, while dehydrated stale bread forms bright regions; the two samples can be easily distinguished.
  3. With 1300 nm fill light only:
    Overall image brightness rises, and contrast between fresh and stale bread is further enhanced.
  4. With 1300 nm filter only:
    Light wavelengths outside 1300 nm are blocked, improving the contrast between fresh and stale bread.
  5. Combined 1300 nm filter + 1300 nm fill light:
    Optimal imaging quality with the clearest separation between fresh and stale bread.

5.2 Quantitative Contrast Analysis

Contrast is calculated to quantitatively evaluate the differentiation capability of the system, using the formula below:
$$Contrast = \frac{I_{max}-I_{min}}{Full\ Grayscale\ Range}$$
Where $I_{max}$ and $I_{min}$ refer to the average grayscale values of stale bread and fresh bread respectively; full grayscale range equals 255 for 8-bit images.

Shooting ConditionGrayscale Value of Fresh BreadGrayscale Value of Stale BreadCalculated Contrast
SWIR1503B10G direct capture106750.12
With 1300 nm fill light only107500.22
With 1300 nm filter only93570.14
Combined 1300 nm filter + fill light110520.23

6. Result Analysis

  1. Function Validation: The SWIR1503B10G SWIR camera successfully distinguishes bread freshness by detecting internal moisture content. Moist fresh bread appears dark, while bread stored for 24 hours with depleted moisture appears bright, enabling clear visual separation.
  2. Phenomenon Summary: Imaging with paired 1300 nm filter and matching infrared fill light delivers the highest contrast of 0.23, producing the best image quality and most reliable freshness identification compared to standalone SWIR shooting or single auxiliary components.
  3. Performance Evaluation: The camera delivers high SNR with clean background noise in images; prominent contrast between fresh and stale bread fully meets the requirements of this inspection scenario.

7. Conclusion

Attostek SWIR1503B10G short-wave infrared camera can reliably inspect bread freshness by measuring moisture content. The combination of a 1300 nm bandpass filter and matched 1300 nm infrared fill light achieves maximum contrast between fresh and stale bread samples. Featuring high SNR and high quantum efficiency, this camera supports fast, non-destructive, on-line freshness inspection across bread production, warehousing and retail workflows.

For practical industrial deployment, simultaneous use of a 1300 nm filter and same-band infrared fill light is recommended to maximize imaging contrast.

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