Reflectivity is one of the difficulties in distinguishing a duplicate hologram (hologram verification) from an original. Because a slight change in lighting condition completely changes the reflection pattern displayed by a hologram, a standardized duplicate hologram detector has yet to be developed.
Researchers have developed a portable, low-cost snapshot hyperspectral imaging (HSI) algorithm-based housing module to distinguish between original and duplicate holograms (hologram verification). The module comprises a Raspberry Pi 4 processor, a Raspberry Pi camera, a display, and a light-emitting diode lighting system with a dimmer.
The researchers developed a visible HSI algorithm that converts an RGB image captured by the Raspberry Pi camera into a hyperspectral image. They chose a region of interest in the spectral image and measured mean gray value (MGV) and reflectivity. When MGV is used as the classification parameter, the results show that shorter wavelengths are best for differentiating holograms (hologram verification), while longer wavelengths are best when reflectivity is used.
The main advantages of this design are:
The researchers intend to use the same hologram verification methodology to distinguish counterfeit currency from genuine currency. The same design could create a NIR-HSI conversion algorithm and a low-cost NIR-HSI module.