Banknote Management System Using Neural Network Classification
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Solution Overview
Problem
Existing banknote management systems face challenges in accurately and efficiently collecting and identifying banknote information, particularly with issues related to orientation, character positioning, data volume, and robustness under conditions of damage or dirt, leading to low identification efficiency and robustness.
Innovation Solution
A banknote management method that collects features using image, infrared, fluorescence, and magnetism, and employs edge detection, image rotation, adaptive binarization, moving window registration, and normalization to improve the accuracy and efficiency of prefix number identification, using a convolutional neural network for classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If simple binarization and size processing are used for character segmentation, then the processing is simple and fast, but the character range is large leading to wrong segmentation and heavy data volume that reduces identification efficiency
Solution Approach 1:
The patent applies segmentation by dividing the banknote image into multiple scanning lines and processing each line independently. The character segmentation is achieved through line-by-line scanning with neural networks, breaking down the large character range into smaller manageable units, which reduces wrong segmentation and decreases the effective data volume for processing.
Solution Approach 2:
The patent introduces a new dimension of processing by using line-by-line scanning instead of processing the entire image at once. This dimensional approach transforms the 2D image processing into a sequence of 1D line processing tasks, reducing the computational burden and data volume while maintaining identification accuracy.
2Measurement precision
If DSP identification method with template matching and neural networks is used, then identification can be achieved, but the network transmission efficiency is limited and identification speed is slow
Solution Approach 1:
The patent applies preliminary action by performing edge detection and orientation correction before the main identification process. The banknote orientation is determined and corrected in advance, and the image is preprocessed with edge detection to highlight character boundaries. This preliminary processing reduces the complexity of subsequent neural network identification and improves overall identification speed.
Solution Approach 2:
The patent replaces traditional mechanical DSP processing with a more efficient neural network-based approach. Instead of using conventional template matching and mechanical image processing methods, the system employs neural networks for orientation determination and character recognition, which significantly improves identification speed while maintaining or enhancing accuracy.
3Measurement precision
If edge detection and orientation correction are performed, then the banknote orientation can be identified, but the rapid slope change caused by banknote delivery cannot be well adapted and slope correction is delayed
Solution Approach 1:
The patent applies continuity of useful action by performing orientation determination and slope correction in a continuous, integrated manner throughout the image processing pipeline. Rather than treating these as separate discrete steps, the system continuously adjusts for slope changes during the scanning and identification process, ensuring that orientation correction keeps pace with rapid slope changes caused by banknote delivery variations.
4Adaptability or versatility
If traditional identification algorithms are used, then they can handle complete banknotes, but the identification robustness of damaged banknotes is low and no specific processing methods are provided
Solution Approach 1:
The patent applies parameter changes by adjusting the neural network parameters and processing thresholds based on the condition of the banknote. For damaged banknotes, the system modifies identification parameters and uses adaptive thresholding to accommodate missing or degraded features. This allows the system to maintain high identification robustness across both complete and damaged banknotes by dynamically adjusting processing parameters.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method achieves high-efficiency and accurate banknote information collection and identification, enhancing robustness and reducing data processing volume, while ensuring fast operation and compatibility with existing equipment like ATMs.
Implementation Method 1
collects, identifies and processes banknote features of banknotes in corresponding services by ways of image, infrared, fluorescence, magnetism and thickness
Implementation Method 2
collects, identifies and processes banknote features of banknotes in corresponding services by ways of image, infrared, fluorescence, magnetism and thickness
Implementation Method 3
collects, identifies and processes banknote features of banknotes in corresponding services by ways of image, infrared, fluorescence, magnetism and thickness
Implementation Method 4
collects, identifies and processes banknote features of banknotes in corresponding services by ways of image, infrared, fluorescence, magnetism and thickness
Data Source
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AI summary
Provided in the present invention is a banknote management method. The method comprises: acquiring, identifying, and processing banknote features by a banknote information processing apparatus, so as to obtain banknote feature information; transmitting the banknote feature information, service information, and information about the banknote information processing apparatus together to a main control server; and the main control server processing the received information and classifying banknotes. Also provided is a banknote management system for the banknote management method. The method of the present invention can enhance robustness of identification while maintaining an operation speed, thus ensuring accuracy and practicability in actual applications.