Medium Recognition Using Color and Size Data
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Solution Overview
Problem
Existing medium recognition systems face challenges in determining the type of a medium quickly and accurately due to complex algorithms, sensitivity to vibration and noise, and high memory requirements for storing characteristic patterns.
Innovation Solution
A medium recognition apparatus that uses a combination of color and size information from a sensor unit, including color and image sensors, to determine the type of a medium by extracting individual color information, correcting skew, and calculating hue, with a determination unit comparing these features to reference data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If characteristic pattern extraction algorithms are used to determine medium type, then recognition accuracy can be achieved, but the algorithm complexity and processing time increase significantly
Solution Approach 1:
The patent extracts only the essential features (color information and size information) from the medium image, rather than performing complete characteristic pattern extraction. This selective extraction of key parameters simplifies the algorithm while maintaining recognition accuracy by focusing on the most discriminative features.
Solution Approach 2:
The patent transforms the complex characteristic pattern recognition problem into a simpler parameter comparison task by changing the representation from detailed image patterns to fundamental parameters (color values and dimensions). This parameter transformation reduces computational complexity while preserving the ability to distinguish medium types.
2Measurement precision
If complete image scanning and characteristic pattern extraction are performed, then medium type determination can be made, but processing time increases
Solution Approach 1:
The patent extracts only color information and size information from the medium image, skipping the time-consuming steps of complete image scanning, filtering, and detailed pattern extraction. This selective feature extraction dramatically reduces processing time while maintaining sufficient accuracy for medium type determination.
Solution Approach 2:
The patent performs partial image processing by extracting only the necessary color and size parameters rather than conducting complete image analysis. This partial action approach processes only the essential features needed for classification, reducing overall processing time while achieving the recognition goal.
3Adaptability or versatility
If characteristic patterns are stored in database for comparison, then medium recognition can be performed, but memory capacity requirements increase
Solution Approach 1:
The patent changes the stored data from complete characteristic patterns to simplified parameter sets (color values and size measurements). This parameter reduction allows the database to store only essential reference values for each medium type, dramatically reducing memory requirements while maintaining recognition versatility.
Solution Approach 2:
The patent uses simplified parameter representations as copies of the essential medium characteristics rather than storing complete image patterns. These parameter copies capture the necessary distinguishing features at a fraction of the storage cost, enabling versatile medium recognition with minimal memory capacity.
4Productivity
If color pattern scheme is used to determine banknote type, then recognition can be performed, but information sufficiency and processing speed are insufficient
Solution Approach 1:
The patent merges color information extraction with size information measurement into a unified recognition approach. By combining these two fundamental parameters, the system achieves sufficient information for accurate medium type determination while processing both features simultaneously, improving recognition speed without sacrificing information completeness.
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
This approach simplifies the recognition process, improves accuracy, and reduces memory requirements, enabling faster and more precise identification of medium types while being less susceptible to noise and vibration.
Implementation Method 1
identifying the shape of the banknote based on sensing data regarding the reflected or transmitted light
Data Source
AI summary
Disclosed is a medium recognition apparatus for determining the type of a medium by using color information obtained by scanning the inserted medium, as well as a method for determining the type of a medium by using the apparatus. Color information and size information obtained by scanning only a partial region of a medium image, the hue of the medium image scanned by the image sensor, or RGB channel color information scanned by the color sensor is compared with pre-stored reference information to determine the type of the medium. This guarantees that the type of the medium is determined quickly and accurately based on simple comparing results.