Edge Text Detection for Mobile OCR
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Solution Overview
Problem
Portable computing devices often capture images with actionable text partially cut off, leading to erroneous actions or user dissatisfaction due to incomplete text processing.
Innovation Solution
Implementing a system where the device detects text proximity to the image edge and uses optical character recognition (OCR) with semantic boosting to determine completeness, waiting for full text capture before invoking actions and providing visual hints to users to adjust the camera view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the device processes text captured in the image immediately, then the processing speed is improved, but the accuracy deteriorates due to incomplete text
Solution Approach 1:
The system performs preliminary detection of text proximity to image edges before initiating full text processing. By analyzing the positions of text bounding boxes relative to image boundaries, the system identifies potentially incomplete text and delays processing until the text is complete, thus resolving the contradiction between speed and accuracy
Solution Approach 2:
The system provides visual feedback to users by displaying indicators (such as colored borders or icons) when text is detected to be incomplete. This feedback mechanism guides users to adjust the camera view to capture complete text, ensuring accurate processing while maintaining efficient workflow
2Measurement precision
If the device waits for complete text capture before processing, then the accuracy is improved, but the productivity deteriorates due to delayed action invocation
Solution Approach 1:
The system automatically detects text completeness and manages the processing workflow without requiring user intervention. It self-adjusts by either proceeding with processing when text is complete or displaying visual cues for user guidance when incomplete, thereby maintaining high productivity while ensuring accuracy
Solution Approach 2:
Visual feedback indicators are displayed to guide users in capturing complete text efficiently. The system provides real-time guidance (such as directional arrows or highlighted regions) to help users quickly adjust the camera view, minimizing delays while ensuring text completeness for accurate processing
3Ease of operation
If the device provides visual hints to users, then the ease of operation is improved, but the device complexity increases
Solution Approach 1:
The visual hinting functionality is implemented as a separate, modular component that extracts only the necessary guidance elements (such as icons, colors, or simple graphical overlays) from the complex image processing pipeline. This modular approach enhances ease of operation while minimizing the impact on overall device complexity
Data Source
AI summary
Approaches to enable a computing device, such as a phone or tablet computer, to detect when text contained in an image captured by the camera is sufficiently close to the edge of the screen and to infer whether the text is likely to be cut off by the edge of the screen such that the text contained in the image is incomplete. If the incomplete text corresponds to actionable text associated with a function that can be invoked on the computing device, the computing device may wait until the remaining portion of the actionable text is captured by the camera and made available for processing before invoking the corresponding function on the computing device.