Automated Video Quality Testing for Set-Top Boxes
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Solution Overview
Problem
Current methods for testing and analyzing set-top boxes (STBs) are inefficient and subjective, relying on human visual inspection, which leads to variable and unreliable quality determinations, making it difficult to standardize video quality assessments and control the pass/fail rates of STBs.
Innovation Solution
A test system utilizing computing devices to receive and analyze video signals from STBs, employing automated testing and data storage in a database, allowing for consistent and efficient testing of multiple STBs simultaneously, using test patterns and reference files to quantify video quality objectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If human-based visual inspection is used to test STB video quality, then testing can be performed with simple equipment, but the testing process becomes slow and the results become subjective and variable
Solution Approach 1:
The patent replaces the mechanical human visual inspection system with an automated electronic testing system that captures video output and compares it against reference images using image processing algorithms. This substitution eliminates the need for human testers while providing objective, quantifiable results and significantly increasing testing throughput.
Solution Approach 2:
The patent introduces an intermediary automated testing system that acts as a mediator between the STB video output and the quality assessment process. This intermediary system captures video frames, processes them through algorithms, and compares them against reference standards, thereby eliminating direct human involvement in the subjective assessment while maintaining standardized quality criteria.
2Adaptability or versatility
If human testers are used to evaluate video quality, then flexibility in judgment can be applied, but standardization and reliability of quality determination deteriorate
Solution Approach 1:
The patent transforms the subjective quality judgment process into an objective parameter-based assessment system. By defining specific image quality parameters and thresholds for comparison against reference images, the system maintains consistent, standardized evaluation criteria that eliminate variability between different testers while ensuring reliable and repeatable quality determinations.
3Measurement precision
If manual testing of each STB is performed individually, then detailed analysis can be conducted, but testing efficiency and cost-effectiveness decrease
Solution Approach 1:
The patent merges multiple testing functions into a single automated system that can evaluate multiple STBs simultaneously. By combining video capture, image processing, reference comparison, and quality assessment into one integrated automated workflow, the system maintains detailed analysis capabilities while dramatically increasing testing throughput and reducing per-unit testing costs.
4Productivity
If automated testing systems are implemented to test multiple STBs simultaneously, then testing efficiency increases, but system complexity and initial cost increase
Solution Approach 1:
The patent designs the automated testing system with universal, multi-functional components that can handle various testing scenarios. The image processing system serves multiple purposes including quality assessment, defect detection, and compliance verification, thereby reducing overall system complexity while maintaining high testing throughput and versatility across different STB models and video standards.
Data Source
AI summary
A method is provided including capturing a frame from a first video device, the frame representing a test pattern and determination is made of at least one captured color for at least one pixel of the captured frame. A reference pixel is provided including at least one reference color, the reference pixel being determined by statistical analysis of the first signals from a population of second video devices that have received the test pattern. A relation is determined between the captured color value and said reference color and the relation is compared with a threshold value. The relation is stored.