Video Processing System for Automated Image Pattern Detection
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Solution Overview
Problem
Manual detection of test patterns in video data is cumbersome and time-consuming, and existing automated methods are inadequate for efficient pattern recognition in video processing systems.
Innovation Solution
A video processing system that receives video data, determines series of video signal value differences for adjacent pixels, detects image transition boundaries, and identifies patterns such as color bars, pillar boxes, and flat fields, with the ability to generate outputs indicating pattern presence and blurriness thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of test patterns is performed, then detection accuracy can be maintained, but processing time and labor effort increase significantly
Solution Approach 1:
The patent replaces manual visual inspection with an automated image processing system that uses digital signal analysis. The system converts video frames to grayscale, applies edge detection algorithms, and automatically identifies test patterns through coordinate analysis, eliminating the need for human operators to manually examine video content while maintaining detection accuracy.
2Productivity
If existing automated methods are used for pattern detection, then processing time is reduced, but detection capability remains inadequate
Solution Approach 1:
The patent segments the video signal processing into distinct stages: frame extraction, grayscale conversion, edge detection, coordinate identification, and pattern recognition. This segmentation allows each stage to be optimized independently, improving overall detection capability while maintaining efficient processing throughput.
Solution Approach 2:
The patent introduces intermediate processing steps including grayscale conversion as a mediator between color video input and edge detection analysis. This intermediary transformation simplifies the data structure and enhances edge detection accuracy, enabling more reliable pattern recognition without significantly increasing processing time.
3Measurement precision
If comprehensive pattern analysis is performed, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent extracts only the essential features needed for test pattern detection: edge coordinates and their spatial relationships. By focusing solely on these critical elements rather than analyzing entire video frames in detail, the system achieves reliable pattern detection with reduced computational complexity and simpler processing requirements.
Data Source
AI summary
A video processing system may include an input for receiving video data including video signal values for a corresponding plurality of image pixels and having an image pattern therein. The system may further include a processor coupled to the input for determining a series of video signal value differences for each pair of adjacent image pixels along at least one direction, detecting at least one image transition boundary based upon the series of video signal value differences, and detecting the image pattern based upon the at least one image transition boundary.