Shared-Screen OCR Text Detection with Automatic Visual Emphasis
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Solution Overview
Problem
Existing videoconferencing and screen sharing applications lack effective methods for automatically detecting and emphasizing important text during presentations, making it difficult for participants to quickly access and engage with shared information.
Innovation Solution
Implementing an optical character recognition (OCR) process to identify text characters in screen captures, associate them with contextual information, and overlay emphasis components, such as highlights or bounding geometries, within the videoconferencing application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If screen sharing is implemented in videoconferencing applications, then information presentation capability is improved, but text accessibility and engagement difficulty worsen
Solution Approach 1:
The patent replaces manual text searching and reading with automated optical character recognition (OCR) technology. The system automatically detects, extracts, and highlights text from shared screens, substituting the mechanical process of manual information search with an automated visual recognition system that identifies and emphasizes relevant text content.
Solution Approach 2:
The patent applies visual emphasis through color changes and highlighting mechanisms. The OCR system identifies detected text and applies visual markers such as colored highlights, bounding boxes, or other graphical emphasis elements to make important text stand out from the background content, thereby improving text accessibility and participant engagement.
2Measurement precision
If manual text searching is used in shared screens, then text detection precision is improved, but time consumption increases
Solution Approach 1:
The patent implements preliminary action by performing automated text detection and extraction in real-time as screens are shared, rather than requiring post-hoc manual searching. The OCR system continuously monitors and processes shared screen content, pre-identifying and highlighting text before participants need to search for it, thereby eliminating time consumption while maintaining detection precision.
Solution Approach 2:
The system performs self-service text detection and extraction automatically without requiring user intervention. The OCR technology autonomously scans shared screens, identifies text content, extracts relevant information, and applies visual emphasis, freeing participants from manual text searching while maintaining high detection precision through automated image processing algorithms.
Data Source
AI summary
In an embodiment, a computer-implemented method is executed using processors of a computer system, and includes receiving a copy of a stored digital image comprising a screen capture of an application window displayed on the computing device while the computing device accesses or executes a videoconferencing application. The computer-implemented method includes executing an optical character recognition (OCR) process on the screen capture of the application window to identify natural language text characters included within the set of digital images, determining, based on the identified text characters, a set of information associated with text characters of the identified text characters, programmatically transmitting instructions for displaying components that can overlay the videoconferencing application executing on the computing device, programmatically instructing the computing device to redisplay the application window along with the components overlaying the videoconferencing application, such that the text characters are displayed as emphasized within the set of digital images.