Banknote Recognition Using Lab Color Space
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Solution Overview
Problem
Conventional banknote recognition systems based on real-time image processing face instability due to distortion and deformation, leading to low recognition rates, especially since they rely on grayscale images that fail to effectively utilize color information.
Innovation Solution
A banknote classification and recognition method utilizing the Lab color space, where RGB images are converted to Lab color space values (Gray a and Gray b), and these values are used in preset formulas to determine banknote denominations, improving recognition accuracy by leveraging color differences between denominations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If geometric features (length and width) are used for banknote recognition, then the recognition process can be performed in real-time, but distortion and deformation occur leading to instability and decreased recognition rate
Solution Approach 1:
The patent changes the recognition parameters from geometric features (length, width) to color space features (Lab color values). By transforming the feature extraction approach to use color information that is invariant to geometric distortion, the system maintains real-time processing capability while significantly improving recognition stability and accuracy.
2Device complexity
If gray difference in single channel gray image is used for recognition, then processing is simpler, but the gray feature difference between some denominations is not significant leading to misrecognition
Solution Approach 1:
The patent transforms the recognition parameters from single-channel gray values to multi-dimensional Lab color space values. This parameter transformation enables the system to capture significant color differences between denominations while maintaining computational efficiency, thereby improving measurement precision without substantially increasing complexity.
Solution Approach 2:
The patent transitions from one-dimensional gray scale recognition to three-dimensional Lab color space recognition (L, a, b channels). This dimensional expansion provides richer feature information for differentiation, allowing the system to distinguish between denominations with similar gray values by utilizing color channel variations.
3Productivity
If single channel grayscale image is used, then the processing is simpler and faster, but color information cannot be effectively utilized resulting in low denomination recognition rate
Solution Approach 1:
The patent changes the image representation parameters from grayscale to color space (Lab) while maintaining efficient processing. By using color values that can be derived from standard RGB images and transformed to Lab space, the system effectively utilizes color information for denomination recognition without sacrificing processing speed.
Data Source
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AI summary
A banknote classification and identification method and device based on a Lab color space, which are used for increasing the recognition rate of face values. The method comprises: acquiring an RGB image of a banknote to be detected; calculating gray values Gray R, Gray G and Gray B of the RGB image in red (R), green (G) and blue (B) wavebands; converting Gray R, Gray G and Gray B into gray values Gray a and Gray b in a Lab color space; and comparing the product of Gray a and Gray b and the difference between the absolute value of Gray a and the absolute value of Gray b with a preset formula to obtain the category of the banknote to be detected.