Omron circles
Omron circles are an example of an element that is present on banknotes of many countries.
Therefore, a special analysis of Omron circles is implemented in the Snowfish, where the dimensions of the circles, the color and the position of the omrons can be analyzed.
Genuine
Offset counterfeits
Offset counterfeit
Inkjet counterfeit
Laser printer counterfei
Omron circles application
- Localize individual circles conform microprint application
- Find pixel profile of individual circles
- Calculate line thickness and center diameter
- Determine ‘Orion’ elements that fulfill Omron requirements
- Determine color of circle
Blind embossing, tactility
In principle, all the security features and other elements that are shown here can be visualized and almost always also can be translated into numbers.
Using the semi-3D view that is produced by the Snowfish, these tactile features can be shown on the screen and measured.
The exact position of the blind embossing can be determined using the Design Element technique.
Once the location of the blind embossing is known, regions of interest can be and the height curve can be determined as shown in the histogram.
Genuine note
Paper tint
Counterfeiters often attempt to replicate off-white paper tints using light overprinting, especially with inkjet or laser printers. However, these methods produce distinct dot patterns that reveal their artificial origin:
- Inkjet prints show irregular, seemingly random dot distributions.
- Laser prints exhibit geometric, repetitive patterns.
Thanks to Snowfish’s high resolution, individual ink dots can be clearly resolved—enabling reliable detection through multiple analytical approaches:
- Dot-size distribution analysis: Most counterfeit dots measure 2–4 pixels in size, creating a identifiable signature.
- Pattern recognition: Optional algorithms can identify specific printer types based on their characteristic output.
By automating these checks, Snowfish turns a traditionally subjective inspection into a fast, objective, and scalable counterfeit classification step.
Genuine
Inkjet counterfeit
Laser printer counterfeit
OVMI
Presence OVMI can be measured in the semi 3D images.
The tiny mirrors oriented to the left side reflect more light, the tiny mirrors oriented to the right reflect less light.
The left oriented are significantly lighter (‘white), the right oriented are darker (‘black’)
Counterfeit notes do not have the tiny mirrors and will have no darker and lighter spots.
The light and dark spots can be measured using the percentile measurement of reflection.
The ratio between percentile 99 and percentile 1 can be used as the
indicator, where a threshold of 3.0 could be used.
Classification system
- Based on earlier measured properties, the measured counterfeits can be combined into a classification algorithm, using Artificial Intelligence techniques
SF Counterfeit Classification Technology
Classify in a fast and easy way and discover new counterfeiting technology trends (Early warnings)
- The figure shows clustering using two components of the properties measured in a set of counterfeit notes
- The groups of dots (except red ones) represent known counterfeit classes
- One banknote defined as a counterfeit found far away (outlier) could represent a new counterfeit technology trend, an EARLY WARNING!
Quality rate for counterfeits
- Quality rate concept is developed in order to assign a ‘quality of counterfeiting’ to a counterfeited note.
- Until now most attention has been given to the reproduction of the security features
- But as different studies have shown, public is hardly aware of security features.
- The quality rate as seen by the Snowfish team, is to assign a value to the quality of the reproduction of print and paper. More specifically the color, the line quality and the quality of the microprint.
Overall quality rating based on color, line quality and readability
