Video Processing Device Frozen Video Detection
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Solution Overview
Problem
Existing video processing devices face a decrease in data transfer rate when detecting frozen video, which affects the performance of display systems.
Innovation Solution
A video processing device that generates and embeds frame numbers and cyclic redundancy check (CRC) symbols into video data blocks, allowing for efficient detection of frozen video without compromising data transfer rates by using a processor to manage data blocks and generate abnormality determination signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If frame numbers are assigned to video data to detect frozen video, then frozen video detection capability is improved, but data transfer rate decreases
Solution Approach 1:
The video data is divided into data blocks of a predetermined size, and frame numbers are embedded only in specific portions of each data block rather than processing the entire video data stream. This segmentation approach enables frozen video detection while minimizing the impact on data transfer rate by limiting the processing overhead to only necessary portions of the data.
Solution Approach 2:
The determination part checks frame numbers only for a predetermined number of data blocks instead of examining every single data block in the video stream. This partial action approach provides sufficient frozen video detection capability while reducing the processing load and maintaining higher data transfer rates compared to complete inspection of all data blocks.
2Measurement precision
If frame numbers are embedded in every data block, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The video data stream is segmented into manageable data blocks with frame numbers embedded in specific portions of each block. This segmentation reduces processing complexity by breaking down the continuous video data into discrete, manageable units that can be processed independently and efficiently.
Solution Approach 2:
Frame numbers are embedded in specific portions of data blocks rather than uniformly throughout the entire data block. This local quality approach concentrates the detection-related information in specific locations, making the processing more efficient and reducing the overall complexity of the system while maintaining detection accuracy.
3Reliability
If all data blocks are inspected for frame numbers, then detection reliability is improved, but processing time increases
Solution Approach 1:
The system inspects frame numbers in a predetermined number of data blocks rather than examining every single data block. This partial inspection approach maintains sufficient detection reliability by checking enough samples to detect frozen video conditions while significantly reducing the processing time required compared to complete inspection of all data blocks.
Solution Approach 2:
The determination part skips inspecting certain data blocks and only checks frame numbers in a subset of predetermined blocks. This skipping approach allows the system to rush through the detection process quickly while still maintaining reliable frozen video detection capability, thereby reducing processing time without sacrificing detection reliability.
Data Source
AI summary
A video processing device is configured to: generate a frame number which represents a frame to which video data belong and a value of which changes between consecutive frames; for each data block of a predetermined size in the video data, embed the frame number in a portion of the data block; write, in a frame order, the video data into a memory by using a data block as a unit; successively read data blocks written into the memory; and generate an abnormality determination signal indicating frozen video in a case where a state in which the frame number in the data block currently read does not change from the frame number in the data block read last time continues for a predetermined number of times or more.