Banknote authentication method based on random forest

Abstract

The invention relates to the field of banknote anti-counterfeit research, and specifically relates to a banknote authentication method based on a random forest. A multispectral image of a banknote acquired based on a sensor is processed using an embedded equipment chip. The method comprises the following steps: carrying out feature extraction in a specific area cut out based on an acquired original image and a gradient image thereof to get multiple features needed for classification; creating a single decision tree, and carrying out node splitting from a root node to leaf nodes; and building a random forest including multiple decision trees. Through the scheme, a random forest classifier which can be realized on embedded equipment is established, banknote authentication can be performed on a currency counter using a DSP chip as a processor, the banknote authentication of the currency counter is improved, counterfeit banknotes mixed in real ones can be accurately identified and classified, computation is quick, and the real-time requirement of the equipment is satisfied. The defect that the traditional authentication method has weak ability to identify unknown counterfeit banknotes and new currencies is overcome.

Description

technical field [0001] The invention belongs to the field of banknote anti-counterfeiting research, in particular to a banknote authentication method based on random forest. Background technique [0002] The banknote counter is a mechatronic device that automatically counts the number of banknotes and identifies counterfeit currency. In offices with a large amount of cash circulation, the banknote counter has become an indispensable device. Counterfeit banknote identification is a vital function of a banknote counter. There are a variety of anti-counterfeiting information on banknotes. Traditional banknote counters use features such as magnetic distribution, infrared penetration, and paper fluorescence to identify counterfeit. With the development of printing technology, copying technology and electronic scanning technology, the production level of counterfeit banknotes is getting higher and higher, and the traditional identification technology of banknote counters can no l...

AI Technical Summary

Problems solved by technology

In the traditional multi-spectral image identification technology, the statistical information of the banknote image, such as pixel histogram, mean value, variance, etc., is used to identify the method, and the traditional "authentication by false" technology is applied. This identification method is easily affected by different points. Influenced by the drawing environment of banknote machine equipment, the identification result is limited by the setting of experience value, so the ability to identify unknown counterfeit currency and new currency is weak

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