Gradient Privacy Masks for Seamless Video Obfuscation
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Solution Overview
Problem
Current digital video monitoring systems use uniform privacy masks that draw attention to masked areas, failing to seamlessly integrate with the rest of the image, thus compromising image integrity and privacy.
Innovation Solution
The implementation of gradient privacy masks that dynamically obscure image regions based on pixel-specific obscurity levels, using techniques like blurring and varying opacity, allowing for adaptive and detailed masking without drawing attention to the mask itself.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If uniform privacy masks are used to obscure sensitive areas, then privacy protection is achieved, but the mask draws attention to itself and compromises image integrity
Solution Approach 1:
The patent applies different obscurity levels to different regions within the masked area. Instead of uniform masking, the system creates gradient masks where certain sub-regions have higher obscurity than others, allowing the mask to blend more naturally with the surrounding image while still protecting sensitive information.
Solution Approach 2:
The system dynamically adjusts the obscurity parameter across different spatial locations within the mask region. By varying the degree of obscuration as a continuous parameter rather than applying a fixed uniform mask, the system achieves seamless integration with the rest of the image, reducing the visual impact of the mask itself.
2Ease of manufacture
If manual mask creation is used during setup, then mask configuration is simple, but the mask cannot adapt to different objects or regions dynamically
Solution Approach 1:
The patent transforms static manual masks into dynamic adaptive masks that automatically adjust based on image content. The system uses object detection algorithms to identify different regions and objects in real-time, then dynamically applies appropriate masking strategies without requiring manual reconfiguration for each scenario.
Solution Approach 2:
The system enables masks to automatically configure themselves based on predefined rules and detected image content. Instead of requiring operators to manually adjust masks for different situations, the system autonomously determines which regions to mask and with what degree of obscurity, based on object detection results and configurable privacy rules.
3Reliability
If high obscurity levels are applied to all masked regions, then privacy protection is maximized, but important details may be lost and the mask becomes more noticeable
Solution Approach 1:
The system applies different obscurity levels to different sub-regions within the masked area based on their importance and sensitivity. Critical sensitive regions receive higher obscurity levels for maximum privacy protection, while less sensitive areas maintain lower obscurity to preserve image quality and reduce mask visibility.
Solution Approach 2:
Instead of applying uniform high obscurity across all masked regions, the system selectively applies high obscurity only where absolutely necessary for privacy protection. This partial application of maximum obscurity preserves image quality in non-critical areas while maintaining strong protection where needed.
Data Source
AI summary
An apparatus and a method implemented in a computer system for obscuring a first region of an image composed by a plurality of pixels. The method comprising obtaining a mask, the mask defining an obscurity level for each pixel in the first region of the image, and obscuring pixels in the first region of the image based on the mask's obscurity level for each pixel.