Face Authentication Collation Device Using Brightness Distribution Analysis
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Solution Overview
Problem
Existing face authentication techniques are vulnerable to impersonation using photographs, requiring complex operations or multiple lighting changes, which compromises convenience and simplicity.
Innovation Solution
A collation device and method that uses a processor to detect brightness distribution in captured images and apply determination conditions to differentiate between real and photographic images, allowing for easy fraud prevention by eliminating photographic images based on brightness criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If brightness distribution analysis is used to eliminate photographic images, then authentication security is improved, but device complexity increases
Solution Approach 1:
The patent extracts and analyzes only the brightness distribution characteristics from captured images to distinguish between real faces and photographs. By focusing specifically on brightness distribution patterns rather than performing comprehensive image analysis, the system achieves effective fraud detection while maintaining relatively simple processing requirements.
Solution Approach 2:
The patent changes the analysis parameter from comprehensive image feature extraction to specific brightness distribution analysis. This parameter change simplifies the processing complexity while maintaining authentication security, as brightness distribution provides sufficient discrimination power between real faces and photographs without requiring complex multi-parameter analysis.
2Reliability
If predetermined operations are requested during imaging, then fraud detection capability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent enables the system to automatically detect whether a captured image is a photograph or a real face by analyzing brightness distribution characteristics. This self-service capability eliminates the need for users to perform predetermined operations such as blinking or changing orientation, thereby maintaining authentication convenience while improving fraud detection capability.
3Reliability
If multiple lighting conditions are used for imaging, then fraud detection capability is improved, but loss of time increases
Solution Approach 1:
The patent segments the fraud detection process into a single brightness distribution analysis step performed on a single captured image, rather than requiring multiple images under different lighting conditions. This segmentation approach maintains fraud detection capability while significantly reducing the time required for authentication.
4Ease of manufacture
If brightness distribution analysis is applied, then ease of manufacture is improved, but measurement precision requirements increase
Solution Approach 1:
The patent employs brightness distribution analysis that can be implemented using standard imaging devices without requiring specialized or expensive equipment. The method uses readily available computational resources to perform the analysis, making the system easy to manufacture and deploy while achieving sufficient measurement precision through algorithmic approaches rather than hardware complexity.
Data Source
AI summary
A collation device is configured to include a processor, and a storage unit that stores a predetermined determination condition in advance, under which a photographic image which is an image obtained by imaging a photograph of the subject is capable of being eliminated, the processor is configured to detect brightness distribution of a face image obtained by imaging an authenticated person with an imaging unit, determine whether or not the detected brightness distribution satisfies a determination condition, and perform face authentication using the face image satisfying the determination condition.