Privacy Protected Image Generation via Automatic Obscuring Processor
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Solution Overview
Problem
Image capture devices used for public safety and security often raise privacy concerns due to the potential unauthorized access or distribution of personal identifiable information, such as facial features, license plate numbers, and name tags, which existing technologies have not adequately addressed.
Innovation Solution
A digital image receiver system with an automatic obscuring processor that detects and obscures identity-correlated regions in images, using techniques like the Viola Jones algorithm, neural networks, and reversible or irreversible obscuration methods to generate privacy-protected images without storing the original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image capture devices capture detailed information for public safety and security purposes, then the ability to identify individuals and objects is improved, but privacy concerns and risk of unauthorized access to personal identifiable information increase
Solution Approach 1:
The system performs preliminary obscuration of personal identifiable information at the point of capture before the image data can be accessed or distributed. By automatically detecting and obscuring faces, license plates, and other PII in real-time during the imaging process, the system prevents privacy risks from arising in the first place, rather than attempting to control access to already-captured sensitive data
Solution Approach 2:
The system extracts and removes personal identifiable information from the captured image by applying selective obscuration to identified PII regions. This allows the system to retain useful security information (such as detecting that a face is present) while removing the harmful identifiable details (specific facial features), effectively separating the useful signal from the privacy-risk information
2Reliability
If real-time obscuration processing is applied to protect privacy, then privacy protection effectiveness is improved, but processing time and computational resources increase
Solution Approach 1:
The system applies partial action by selectively obscuring only the specific regions containing personal identifiable information (faces, license plates, name tags) rather than obscuring entire images or processing all pixels uniformly. This targeted approach maintains privacy protection effectiveness while significantly reducing the computational burden and processing time compared to blanket obscuration methods
Solution Approach 2:
The system replaces traditional manual or post-processing obscuration methods with automated real-time processing using machine learning algorithms and digital signal processing. This substitution enables the obscuration to occur during image capture at speeds suitable for moving pictures and live feeds, eliminating the time loss associated with batch processing or manual review
Data Source
AI summary
A system for generating a privacy protected image. The system may have a detection logic and obscuring logic configured to detect one or more identity-correlated object categories. The system may provide automatic selection of a type of obscuring to be used based on the detected category; wherein said automatic selection includes automatically selecting among a plurality of different, category specific types of reversible obscuring. The detection logic and obscuring logic may include an automatic category-specific selecting between irreversible obscuring and reversible obscuring. The system may comprise a privacy protected image output logic configured to generate the privacy protected image.