Wavelet Packet Transform for Banknote Texture Discrimination
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Solution Overview
Problem
Current methods for authenticating security documents, particularly banknotes, face challenges in robustly distinguishing between intaglio-printed textures and commercial offset printed textures, especially in efficiently differentiating high-quality commercial prints from authentic intaglio prints.
Innovation Solution
The method employs a two-dimensional shift-invariant wavelet packet transform (2D-SIWPT) with an incomplete wavelet packet tree decomposition, using the Best Branch Algorithm to identify the node with the highest information content, which effectively discriminates between intaglio and commercial offset printed textures by analyzing variance and excess in wavelet coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing methods are used to authenticate security documents, then the authentication process is simple to implement, but the ability to discriminate between intaglio and commercial offset printed textures is insufficient
Solution Approach 1:
The patent applies wavelet packet transform to decompose the image into multiple frequency sub-bands, segmenting the texture information into different frequency components. This segmentation enables precise analysis of specific texture characteristics that distinguish intaglio from commercial offset printing, thereby improving measurement precision without requiring complex hardware modifications
Solution Approach 2:
The patent transforms the image from spatial domain to frequency domain using wavelet packet transform, changing the parameter representation from pixel values to wavelet coefficients. This parameter transformation reveals subtle texture differences that are not visible in the original image, enhancing discrimination capability while maintaining computational feasibility
2Reliability
If high-quality commercial offset prints are analyzed, then the printing quality is high and visually similar to intaglio prints, but the discrimination between authentic and counterfeit becomes more difficult
Solution Approach 1:
The patent moves the analysis from the visual spatial dimension to the frequency dimension using wavelet packet transform. In the frequency domain, subtle texture differences between high-quality commercial offset prints and authentic intaglio prints become distinguishable through statistical analysis of wavelet coefficients, thereby improving authentication reliability without increasing visual inspection difficulty
Solution Approach 2:
The wavelet packet transform acts as an intermediary that extracts and amplifies subtle texture characteristics from the image. By transforming the image into wavelet coefficients and analyzing their statistical properties (variance, entropy), the method reveals hidden differences between authentic and counterfeit prints that are imperceptible in the original image, enhancing detection capability
3Ease of operation
If a portable device is used for authentication, then the device is convenient to operate, but the processing power and computational capability are limited
Solution Approach 1:
The patent extracts only the essential authentication features from the image by analyzing specific statistical properties of wavelet coefficients (variance, entropy, mean) in selected frequency sub-bands. This extraction approach reduces the computational load significantly compared to processing the entire image, enabling efficient authentication on portable devices with limited processing power while maintaining high discrimination accuracy
Data Source
AI summary
There is described a method for checking the authenticity of security documents, in particular banknotes, wherein authentic security documents comprise security features (41-49; 30; 10; 51, 52) printed, applied or otherwise provided on the security documents, which security features comprise characteristic visual features intrinsic to the processes used for producing the security documents. The method comprises the step of digitally processing a sample image of at least one region of interest (R.o.I.) of the surface of a candidate document to be authenticated, which region of interest encompasses at least part of the security features, the digital processing including performing a decomposition of the sample image by means of wavelet transform (WT) of the sample image. Such decomposition of the sample image is based on a wavelet packet transform (WPT) of the sample image, preferably a so-called two-dimensional shift invariant WPT (2D-SIWPT).