Image Data Variation Region Masking for Privacy Protection
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Solution Overview
Problem
Existing information processing systems face challenges in detecting and mitigating noise during the recording and reading of image data, particularly when personal information is involved, as noise can lead to the inclusion or exclusion of sensitive information, and existing methods do not effectively manage this issue without revealing confidential data.
Innovation Solution
An information processing apparatus that compares image data with read data to identify variation regions, which may contain noise or personal information, and uses a mask processing module to render these regions invisible, ensuring that personal information is not exposed during the output process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image data is compared with read data to detect noise and variation regions, then measurement precision is improved, but the complexity of the device increases due to additional processing modules
Solution Approach 1:
The patent segments the image processing task into distinct functional modules: a comparison unit that compares image data with read data to identify variation regions, and a mask processing unit that selectively masks these regions. This segmentation allows each module to perform its specific function efficiently, improving noise detection precision while managing device complexity through modular design.
Solution Approach 2:
The comparison unit performs preliminary identification of variation regions containing noise or personal information before the final output stage. By detecting and marking these regions in advance, the system can apply masking operations subsequently, ensuring that noise is detected with high precision without requiring complex real-time processing during output.
2Object-affected harmful factors
If variation regions containing personal information are identified and masked, then privacy protection is improved, but information loss occurs in the masked regions
Solution Approach 1:
The mask processing unit applies local quality differentiation by selectively masking only the variation regions that contain personal information or noise, while leaving the rest of the image data unmasked and fully visible. This ensures privacy protection for sensitive regions without causing unnecessary information loss in other areas, maintaining the balance between privacy protection and information completeness.
Solution Approach 2:
The mask processing unit acts as an intermediary between the comparison unit and the output stage. It receives the identified variation regions from the comparison unit and applies selective masking, serving as a mediator that protects personal information while preserving the integrity and completeness of non-sensitive information in the output image.
3Reliability
If the comparison unit processes all image data to detect noise, then reliability is improved, but processing time increases
Solution Approach 1:
The comparison unit extracts only the critical variation regions that contain noise or personal information from the entire image data, rather than processing every pixel uniformly. By focusing computational resources on identifying and masking these specific regions, the system maintains high noise detection reliability while significantly reducing the overall processing time compared to exhaustive full-image analysis.
Data Source
AI summary
Provided is an information processing apparatus including a comparison unit that compares image data with read data obtained by reading a medium on which an image of the image data is formed, an acquisition unit that acquires a variation region that varies in plural image data items or in plural read data items, and an output unit that outputs a comparison result of the comparison unit such that the variation region is in an invisible state.