Real-Time Video Redaction Using OCR and Object Detection
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Solution Overview
Problem
Existing video redaction solutions for sensitive information in video streams are inefficient and prone to leaks, particularly in real-time environments, as they rely on offline processing of recorded video files.
Innovation Solution
Implementing computer vision-based middleware that processes video streams in real-time to identify and redact sensitive information using object detection models, machine-readable tags, and optical character recognition, with options for masking or obscuring sensitive content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If offline processing on recorded video files is used, then sensitive information can be redacted, but there is potential for leaking sensitive information from the original video and real-time protection is not achieved
Solution Approach 1:
The system performs preliminary redaction actions on video streams in real-time before the video is distributed or stored. By processing the video stream as it is being captured or transmitted, the sensitive information is redacted proactively rather than reactively after the fact, preventing any potential leakage while maintaining real-time operation.
Solution Approach 2:
The patent introduces an intermediary processing layer between video capture and video distribution/storage. This intermediary system analyzes the video stream, identifies sensitive information using OCR and object detection, and applies redaction before the video reaches its destination or is stored, thus breaking the direct path that could lead to information leakage while enabling real-time protection.
2Reliability
If real-time video stream processing is implemented, then sensitive information can be protected in real-time, but processing complexity and computational resources increase
Solution Approach 1:
The video processing system is segmented into distinct functional modules: video stream reception, object detection, OCR processing, sensitive information identification, and redaction application. Each module handles a specific task independently, which simplifies the overall system architecture, enables parallel processing, and reduces the computational burden on any single component while maintaining real-time performance.
Solution Approach 2:
The patent replaces manual or post-processing redaction methods with automated computer vision-based systems. Machine learning models for object detection and OCR algorithms automatically identify and redact sensitive information without human intervention, substituting complex mechanical or manual processes with intelligent automated systems that are more efficient and scalable.
3Measurement precision
If comprehensive object detection and OCR are used to identify sensitive information, then redaction accuracy improves, but processing speed and computational load increase
Solution Approach 1:
The system applies partial processing by focusing OCR and detailed analysis only on regions containing detected objects or text, rather than analyzing the entire video frame uniformly. This selective approach maintains high detection accuracy for sensitive information while significantly reducing the overall computational load and processing time, as most of the frame may not contain sensitive content requiring intensive analysis.
Solution Approach 2:
The video processing system operates in periodic cycles, alternating between rapid frame capture and intensive analysis periods. During normal operation, frames are processed at high speed with lightweight detection; when objects or text are detected, the system transitions to a more intensive analysis mode for accurate sensitive information identification, then returns to rapid processing. This periodic modulation maintains both accuracy and speed.
Data Source
AI summary
Systems and methods for automatic redaction of sensitive information from video streams are disclosed. According to one embodiment, a method for automatic redaction of sensitive information from video streams may include: (1) receiving, by an image processing computer program executed by an electronic device, a video stream of an area; (2) identifying, by the image processing computer program, an object capable of having sensitive information thereon in the video stream of the area; and (3) redacting or obscuring, by the image processing computer program, the object in the video stream.