Video Window Edge Detection for Display Space Optimization
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Solution Overview
Problem
Conventional display technologies waste screen space and reduce image resolution due to the need for black borders and non-video backgrounds when displaying images with mismatched aspect ratios, leading to inefficient use of display real estate and resources.
Innovation Solution
A method to automatically determine the location of video window edges in a displayed image by dividing the frame into regions and evaluation rectangles, calculating realness indices, and iteratively refining the location of edges to identify transitions between synthetic and real image areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If black borders and non-video backgrounds are used to accommodate aspect ratio mismatches, then the display can show images in non-native formats, but screen space is wasted and image resolution is reduced
Solution Approach 1:
The patent extracts and removes the non-video border areas (black bars, match boxes) from the display frame, isolating only the actual video content region. This allows the system to identify and process only the meaningful video areas, eliminating waste of display real estate while maintaining compatibility with various aspect ratios.
Solution Approach 2:
The patent segments the display frame into multiple regions, evaluating each region to determine whether it contains video content or is a non-video border. By dividing the frame and selectively processing only video-containing regions, the system maximizes effective display area while preserving adaptability to different formats.
2Adaptability or versatility
If black borders and non-video backgrounds are used to accommodate aspect ratio mismatches, then the display can show images in non-native formats, but image resolution is reduced
Solution Approach 1:
The patent extracts the actual video content from the entire frame by identifying and removing non-video border regions. This extraction process ensures that video enhancement and processing operations are applied only to the genuine video areas, preserving maximum image resolution and preventing degradation in the extracted video regions.
Solution Approach 2:
The patent applies different processing qualities to different regions: video enhancement and processing are applied with high quality only to regions containing actual video content, while non-video border regions are excluded from processing. This local quality approach maintains high resolution where it matters while avoiding wasted computational resources on non-video areas.
3Manufacturing precision
If video enhancement or processing is applied to frames with black borders, then image quality can be improved, but computing and memory resources are wasted in blank areas
Solution Approach 1:
The patent extracts and identifies the precise boundaries of video content within the frame by evaluating regions for video characteristics. Once video regions are extracted from the frame, video enhancement and processing operations are applied exclusively to these identified video areas, eliminating waste of computing and memory resources on non-video border regions while maintaining improved image quality where applicable.
Solution Approach 2:
The patent applies video enhancement and processing operations with high quality only to regions containing actual video content, as determined by regional evaluation. Non-video border regions are excluded from processing, optimizing the balance between image quality improvement and computational resource efficiency by applying processing locally only where beneficial.
Data Source
AI summary
The invention provides for automatically identifying the location of a displayed video window based upon a characterization of selected portions of the image for realness based upon a distribution of luminance values for the selected portions. The image is then searched mathematically for a large rectangle of realness, and if found, a similar operation is performed in a smaller rectangle around each of the edges of the large rectangle, in turn, zooming in to a resolution of one pixel, thus identifying the position of the edge. This process can be repeated as often as necessary in order to maintain a fix on the edges of the video window.