Generative Image Transformation for PII-Obscured ADAS Analysis
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Solution Overview
Problem
Existing image processing technologies struggle to effectively obscure personally identifiable information (PII) and location-specific data while maintaining the usability of images for analysis, particularly in vehicle systems like advanced driver assistance systems (ADAS).
Innovation Solution
A system utilizing a visual generative model to modify images with intended alterations, such as text translation, and a validation algorithm to assess the modification's effectiveness, ensuring the image is either deleted or stored based on achieving the intended alteration, thus obscuring PII and location-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional image processing methods are used to obscure PII, then anonymity is improved, but image usability for analysis deteriorates
Solution Approach 1:
The system creates a synthetic copy of the original image using a visual generative model. This synthetic image preserves the structural and contextual information needed for ADAS analysis while replacing PII-containing objects (faces, license plates, signs) with synthesized alternatives that maintain visual plausibility without containing real personal or location data.
Solution Approach 2:
The system identifies and extracts specific PII-containing objects (faces, license plates, text signs) from the original image. These extracted regions are then replaced with synthesized content generated by the visual generative model, separating the PII removal function from the overall image processing workflow.
2Object-affected harmful factors
If visual generative model modifies objects in images, then PII obscuring is improved, but modification effectiveness verification becomes complex
Solution Approach 1:
The system implements a feedback loop where the validation algorithm analyzes the synthetic image to verify that PII obscuring was successful. The validation results feed back into the system to determine whether the synthetic image should be stored (if validation fails) or discarded (if validation succeeds), creating a closed-loop verification process.
Solution Approach 2:
The validation algorithm performs thorough analysis of modified regions to ensure PII is adequately obscured. Rather than checking only for complete removal, the system uses multiple validation criteria including detecting whether synthesized content resembles original PII, ensuring sufficient obscuring effort is applied even if it increases computational complexity.
3Reliability
If synthetic images are stored for failed validations, then data retention is improved, but storage of potentially useful images increases
Solution Approach 1:
The system performs validation checks before finalizing storage decisions. By preliminarily assessing whether the synthetic image successfully obscures PII through the validation algorithm, the system avoids storing images that fail to meet anonymity requirements, preventing waste of storage space on inadequate anonymization attempts.
Solution Approach 2:
The system changes the state of synthetic images based on validation results: images passing validation are marked for storage with success indicators, while failed images are either discarded or flagged for reprocessing. This parameter-based classification optimizes storage utilization by retaining only successfully anonymized images.
Data Source
AI summary
A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive an original image generated by a camera; execute a visual generative model prompted to generate a synthetic image that is a re-creation of the original image with an intended modification of objects of a preset type in the original image, the synthetic image including an actual modification resulting from the intended modification, the actual modification obscuring an original appearance of the objects of the preset type in the synthetic image; in response to the actual modification achieving the intended modification, delete the synthetic image; and in response to the actual modification not achieving the intended modification, store the synthetic image.