Intelligent identification method of banknote serial number based on dsp

Abstract

The present invention relates to the technical field of serial number identification, in particular to a DSP-based intelligent identification method for banknote serial numbers, the steps of which include: collecting images of banknotes; discriminating information such as currency type, currency value, front and back, and inversion of banknotes; Cut out the 1 / 4 image containing the serial number from the acquired banknote image; cut the 1 / 4 image to segment the image containing only the banknote part; roughly locate the serial number area of ​​the image of the banknote part in turn, Accurate positioning; obtain the binary image of the serial number area; separate the character image in the image of the serial number area, compare it with the character template image, and calculate the similarity to identify the character in the character image; for the identified Skeleton feature extraction is performed on the character image whose characters are confusing characters, and the bone feature is used for secondary discrimination to confirm the character corresponding to the character image; combined with the template comparison result and the bone feature discrimination result, the recognized serial number character is output.

Description

technical field [0001] The invention relates to the technical field of serial number identification, in particular to a DSP-based intelligent identification method for banknote serial numbers. Background technique [0002] Most of the current mainstream serial number recognition methods use a single algorithm such as artificial neural network, bone feature, and feature point matching to realize the recognition of the serial number. [0003] Chinese patent publication number is CN105261110A invention patent discloses a kind of efficient DSP banknote serial number recognition method, and its specific steps are: [0004] a) Collect banknote images and find edge points of banknotes; [0005] b) Discharge the abnormal edge points found at the edge of the banknote, and fit the edge straight line to obtain the slope and intercept of the upper, lower, left and right sides of the banknote; [0006] c) Identify the face and direction of the banknote; [0007] d) Locate the serial n...

AI Technical Summary

Problems solved by technology

[0011] 1. The edge calculation method is complicated. The banknotes used in various countries are usually rectangular, that is, the upper and lower sides are parallel, and the left and right sides are parallel. When using the above method, a large number of edge points need to be sampled to fit the straight line equations of all edges. There is redundancy in its calculation amount;

[0012] 2. The artificial neural network has a large amount of calculation, and the neural network model commonly used for character discrimination is at least a 3-4 layer model, that is, at least including the input layer, output layer and intermediate layer

If dimensionality reduction is not performed, the number of points in the input layer of the algorithm is w c × h c The number of nodes in the output layer is 34, and there are more than 2 layers of intermediate layers, so there are a large number of floating point operations, and the performance requirements and budget real-time requirements of DSP are very high, which cannot be achieved by general systems.

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