Video Abnormality Detection via Luminance Analysis
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Solution Overview
Problem
Existing video processing technologies fail to efficiently detect and alert for video abnormalities such as extended black frames and freeze frames during transmission and playback, leading to unsatisfactory viewing experiences and increased costs due to labor-intensive quality assurance.
Innovation Solution
The solution involves comparing luminance data for pixels to a threshold value to detect black frames and analyzing pixel differences between consecutive frames to identify freeze frames, with counters triggering alarms when predefined thresholds are exceeded, allowing for automatic detection and notification of abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If labor-intensive quality assurance is employed to detect video abnormalities, then detection reliability is improved, but productivity deteriorates due to delays and increased costs
Solution Approach 1:
The patent replaces manual quality assurance operations with an automated electronic detection system that compares luminance data of current frames against previous frames to identify abnormalities such as black screens and freeze frames, thereby maintaining detection reliability while eliminating labor-intensive processes and their associated delays
Solution Approach 2:
The system performs self-detection of video abnormalities by automatically analyzing frame data without requiring external human intervention, enabling continuous processing and eliminating the productivity bottlenecks caused by manual quality assurance
2Measurement precision
If manual quality assurance is used to avoid abnormalities, then detection precision is improved, but loss of time increases due to delays in final playback
Solution Approach 1:
The system performs preliminary detection of video abnormalities during the video ingest or playback process itself, comparing frame luminance data in real-time to identify issues before final playback, thereby maintaining detection precision while eliminating delays in the video delivery timeline
3Productivity
If automated detection is implemented, then productivity is improved by reducing human interaction, but device complexity increases
Solution Approach 1:
The patent extracts only the essential luminance data from video frames and compares it against simplified criteria (frame-to-frame luminance differences and absolute luminance thresholds) to detect abnormalities, thereby achieving automated detection with minimal processing complexity and maximum productivity
Data Source
AI summary
Methods and apparatuses to detect presence of undesirable video abnormalities during, for example, video ingest or playback. These undesirable characteristics may include an average picture level that is less than a preset threshold value, or static input, in which the content does not change over a significant number of frames. Detection of abnormalities results in an alarm to a system operator. Analysis and alarm may occur automatically during processing of video data streams. The same abnormalities may be detected during playback of the image data.