Banknote Validation Using Ratio Image Data to Reduce Intensity Variation
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Solution Overview
Problem
Conventional media item validation systems face significant challenges due to variations in image intensity across different validation units, leading to compromised genuine note acceptance rates and increased false acceptance rates, primarily caused by differences in sensor calibration and illumination sources.
Innovation Solution
A method and apparatus for generating a validation template that reduces image intensity variation by using ratio image data from multiple illumination channels, segmenting images, extracting feature information, and classifying it with a one-class classifier to determine the validity of media items, thereby improving the true acceptance rate while maintaining low false acceptance rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single reference template is created using conventional validation units, then the validation process is simple, but the genuine note acceptance rate is significantly compromised due to image intensity variations across different validation units
Solution Approach 1:
The validation template is segmented into multiple sub-templates, each corresponding to a specific validation unit. Each sub-template is generated using image data from that particular validation unit, allowing each unit to have its own calibrated reference. This segmentation resolves the intensity variation issue across different units while maintaining manageable complexity through automated template generation.
Solution Approach 2:
The invention changes the parameter representation from a single unified template to multiple unit-specific templates with adjusted intensity parameters. By creating separate templates for each validation unit with their own intensity characteristics, the system adapts to variations in sensor calibration and illumination sources, thereby improving genuine note acceptance rate.
2Productivity
If multiple validation units with different sensors and illumination sources are used, then the system can validate more media items, but image intensity variation occurs leading to compromised validation accuracy
Solution Approach 1:
The validation system is segmented into multiple independent validation units, each with its own reference template. This allows the system to maintain high productivity by validating items across multiple units while ensuring measurement precision through unit-specific intensity calibration and separate reference templates for each unit.
Solution Approach 2:
The invention introduces an intermediary processing layer that normalizes image intensity data before template generation. This intermediary step adjusts and standardizes the intensity parameters from different sensors and illumination sources, enabling consistent validation across multiple units without compromising precision.
3Reliability
If conventional template generation methods are used, then the process is simple, but the true acceptance rate is significantly compromised due to sensor calibration differences
Solution Approach 1:
The system performs preliminary automated template generation for each validation unit before actual validation operations. By pre-generating unit-specific reference templates using automated image processing, the system eliminates the need for manual calibration and reduces on-site setup time, while ensuring high true acceptance rate through precise unit-specific templates.
Solution Approach 2:
The validation units perform self-calibration by automatically generating their own reference templates using their specific sensors and illumination sources. Each unit processes its own image data to create unit-specific templates, making the system self-sufficient and eliminating dependency on centralized calibration, thereby reducing time loss while maintaining high reliability.
4Reliability
If ratio image data from multiple illumination channels is used, then image intensity variation is reduced and true acceptance rate improves, but the validation process becomes more complex
Solution Approach 1:
The invention merges multiple illumination channels into a unified ratio image representation. By combining data from different channels and normalizing through ratio calculations, the system reduces intensity variation and improves true acceptance rate. The merging process is automated, managing complexity through integrated processing rather than separate operations.
Solution Approach 2:
The system transforms the validation parameters by converting raw image intensity values into ratio-based normalized parameters. This parameter transformation reduces the impact of illumination variations and sensor differences, improving reliability. The automated parameter conversion manages complexity by handling the transformation as a single integrated step.
Data Source
AI summary
The present invention provides a method of validating a media item, the method comprising receiving image data corresponding to a plurality of digital images of a media item to be validated, wherein each image is associated with a respective one of a plurality of different channels of an illumination source for illuminating the media item, selecting image data corresponding to two of the plurality of images, dividing a common parameter of the selected image data associated with corresponding locations of the two selected images to create ratio image data representing a ratio image for two different channels of the illumination source, extracting feature information associated with the ratio image, and classifying the extracted feature information with at least one classifier of a validation template to determine whether or not the media item is valid. A computer program and a Self-Service Terminal for validating a media item, such as a banknote, are also provided.