Banknote image recognition method

Abstract

The invention provides a banknote image recognition method which trains a classifier by using a banknote image in a training set, which recognizes the currency type, the nominal value, the orientation, and the version of a banknote image to be tested by using the trained classifier, and which comprises the following steps of: 1) preprocessing the banknote image; 2) acquiring a plurality of image blocks in the banknote image; 3) computing the image feature of each image block in order to constitute feature vectors of the banknote image as the feature vectors of image blocks of the banknote image in the training set or the banknote image to be tested; 4) training the classifier by using the feature vector of each image block of the banknote image in the training set; and 5) inputting the feature vector of each image block of the banknote image to be tested into the classifier to recognize the banknote image. The banknote image recognition method is not required to a local difference between different banknotes but just required to extract corresponding features from the banknote image to perform subsequent recognition.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a banknote image recognition method. Background technique [0002] With the development of economic globalization and trade integration, my country's opening to the outside world has been deepening, and trade exchanges with various countries have become increasingly frequent. At the same time, the increasingly popular outbound travel market has also promoted the rapid development of related businesses such as foreign currency payment and exchange. Therefore, effective management of various foreign currencies is very important. On the other hand, foreign markets also require banknote counters and sorting machines to support automatic multi-currency functions. [0003] For the sorting and counterfeit identification of banknote images, it is first necessary to identify the face value, orientation, and version of banknotes, and secondly, it is also necessary to ident...

AI Technical Summary

Problems solved by technology

However, in multi-currency recognition, or when there are many versions of the Hong Kong dollar currency, the number of templates will be large, so template matching will be time-consuming and affect processing performance; on the other hand, when banknotes have folded or missing edges, or For example, when the length and width of the U.S. dollar are the same but the white borders around it will be offset by printing, the template matching method will easily lead to recognition errors

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