Vision Testing Augmented With Imperceivable Band Signaling
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Solution Overview
Problem
Manual testing of display systems is time-consuming and labor-intensive, and current automated systems, such as optical character recognition, often fail to accurately differentiate between text and symbology, leading to false positives and inefficiencies.
Innovation Solution
A test system that uses a camera to record both visually perceivable and imperceivable images from a display, with a controller employing artificial intelligence and computer vision models to analyze the imperceivable data and guide the analysis of perceivable data, determining compliance and reporting a compliance score based on deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing is used to observe and grade display systems, then testing accuracy can be maintained, but testing time and labor costs increase significantly
Solution Approach 1:
The patent replaces manual visual inspection with an automated optical testing system that uses cameras to capture display output and AI algorithms to analyze the captured images. This substitution of mechanical/physical inspection with automated optical-digital processing maintains measurement precision while dramatically reducing testing time and labor requirements.
Solution Approach 2:
The patent introduces an intermediary AI-based image analysis system between the display output and the testing evaluation. This intermediary processes the visual output through computer vision algorithms, enabling automated decision-making while preserving the accuracy that would otherwise require human expertise.
2Productivity
If optical character recognition is used to automate display testing, then testing speed increases, but false positives increase due to inability to differentiate text from symbology
Solution Approach 1:
The patent changes the analysis parameters from simple character recognition patterns to multi-parameter visual feature analysis including text characteristics, symbology patterns, spatial relationships, and contextual information. This parameter expansion enables the system to distinguish between text and symbology, maintaining high testing speed while eliminating false positives.
Solution Approach 2:
The patent segments the display content analysis into multiple distinct processing streams: one for text detection, another for symbology recognition, and additional streams for contextual analysis. This segmentation allows each stream to specialize in specific features, improving both speed and accuracy while reducing false positives through cross-validation.
3Device complexity
If visible band imaging only is used for display testing, then system simplicity is maintained, but detection capability is limited to visible content
Solution Approach 1:
The patent extends the detection dimension from visible light spectrum to include infrared and ultraviolet bands. By adding these spectral dimensions, the system can detect imperceivable images and out-of-band signaling without significantly increasing overall system complexity, as the same camera hardware can capture multiple spectral ranges.
Solution Approach 2:
The patent makes the imaging system universal by enabling it to capture both visible and imperceivable content using the same hardware platform. This multi-functionality allows a single camera system to perform both traditional visible content testing and advanced imperceivable image detection, eliminating the need for separate specialized systems.
Data Source
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AI summary
A system and method for determining a compliance of a display (90) to a reference is disclosed. The system includes a camera (104) configured to record images from a display (90), wherein the display (90) is configured to simultaneously display a visually perceivable image and a visually imperceivable image based on an input signal. The test system further includes a controller (116) with processors (140) and a memory (136). The memory (136) has instructions stored upon that instruct the processors (140) to receive the display signal, generate imperceivable image data and perceivable image data based on the display signal, use the imperceivable image data to guide an analysis of the perceivable image data, and determine a compliance score of the display based on a deviation between the perceivable image data and perceivable input of the input signal. The imperceivable image may be a UV image, an infrared image, or an image based on an imperceivable frame rate.