Video System Freeze-Frame Detection via Selective Encoding
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Solution Overview
Problem
Digital video systems often experience freeze-frame conditions due to various failures, which can lead to undetected system faults, posing risks in critical applications like security monitoring and automotive systems, where a static image may not be recognized as a fault until it's too late.
Innovation Solution
A method and video system that selectively encode and decode image frames using different coding schemes to detect freeze-frame conditions by causing noticeable adjustments to image characteristics, such as pixel inversion or color exchange, allowing for visual or automatic detection of errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single coding scheme is used for all image frames, then the processing complexity is low, but freeze-frame conditions cannot be detected
Solution Approach 1:
The video stream is segmented into alternating coded and uncoded frames. The encoder applies different coding schemes to different segments (frames) of the video stream, enabling detection of freeze-frame conditions by comparing coded and uncoded frames while maintaining manageable processing complexity through systematic division of the video stream.
Solution Approach 2:
Different coding schemes are applied to different frames locally within the video stream. Specifically, alternating frames use different coding schemes (e.g., first frame uses scheme A, second frame uses scheme B), allowing local differentiation that enables freeze-frame detection without requiring complex global processing.
2Reliability
If multiple coding schemes are used alternately, then freeze-frame detection is enabled, but processing complexity increases
Solution Approach 1:
The encoder periodically alternates between different coding schemes at regular intervals (e.g., every other frame). This periodic application of different coding schemes enables systematic freeze-frame detection while maintaining predictable processing complexity through regular, repeating patterns rather than arbitrary complexity.
Solution Approach 2:
The system creates coded copies of video frames using different coding schemes. By generating these coded versions and comparing them with uncoded frames or with each other, the system enables freeze-frame detection through relatively simple copy-comparison operations rather than complex analysis.
3Reliability
If freeze-frame detection is implemented, then system reliability improves, but additional processing time is required
Solution Approach 1:
The system performs preliminary encoding of frames with different coding schemes during the normal video encoding process, before freeze-frame detection is needed. This preliminary action embeds the detection capability into the encoding phase itself, so that detection can be performed efficiently during decoding without requiring additional heavy processing time later.
Data Source
AI summary
A method for detecting a freeze-frame condition comprises receiving a sequence of images from at least one digital device; selectively encoding a first subset of the sequence of images using a first coding scheme that causes an adjustment to an image characteristic of the selected images being encoded; selectively encoding a second subset of the sequence of images using a second coding scheme; storing the first encoded subset and second encoded subset; retrieving the stored first encoded subset and second encoded subset; selectively decoding the first subset of the selected images using the first coding scheme and selectively decoding the second subset of the selected images using the second coding scheme to re-create the sequence of images. A freeze-frame condition in the re-created sequence of images is identifiable based on a plurality of decoded images being different with respect to the image characteristic across multiple decoded image frames.