Video Border Detection via Luminance Line Number Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Videos uploaded to video-sharing websites often include constant black or colored borders that occupy space and skew video quality metrics, as existing technologies fail to accurately detect and remove these borders during playback and transcoding processes.
Innovation Solution
A method using a microprocessor to detect the line number where the border changes to video content within frames, updating this line number as necessary, and removing borders from videos while deriving video quality metrics from borderless frames to ensure accurate video quality assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If border detection and removal is implemented, then video quality metric accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the video frame into distinct regions (border area and video content area) by detecting the line number where the transition occurs. This segmentation allows the system to process and evaluate only the relevant video content area, improving metric accuracy while managing complexity through focused analysis.
Solution Approach 2:
The patent performs preliminary border detection and line number identification before conducting video quality assessment. By pre-identifying the border-to-content transition line, the system prepares the data structure in advance, enabling more accurate subsequent analysis without repeating complex detection operations during the actual quality metric calculation.
2Ease of manufacture
If border areas are included in video frames, then ease of manufacture is improved, but loss of information occurs
Solution Approach 1:
The patent extracts and identifies the border area from the video frame by detecting the specific line number where the border transitions to video content. This extraction capability allows the system to separate border regions from actual video content, preventing the loss of valuable display area while maintaining processing simplicity through automated detection.
Solution Approach 2:
The patent applies partial action by focusing detection efforts only on identifying the critical line number where border transitions to content, rather than analyzing every pixel in the frame. This selective approach maintains ease of manufacture while preventing information loss by accurately delimiting the usable video content area.
Data Source
AI summary
Systems and methods for border detection on videos are disclosed herein. The system can include a refinement component that updates a variable as a function of a change in line number, wherein the change in line number is ascertained in response to a change in luminance values and/or chroma values associated with a border and a video area included in a frame associated with an original video. Further, the system also includes a trimming component that, as a function of the variable, crops the border from the frame that includes the video area of the resized original video.