Text Prediction Using Image Capture for Unique Data Entry
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Solution Overview
Problem
Existing predictive text input systems are inconvenient, error-prone, and lack a robust corpus of data for prediction, especially when users need to input unique information such as passwords or codes that are not stored in their device's dictionary, requiring manual re-entry on other devices.
Innovation Solution
A method that uses an image capture device to identify objects and characters in a captured image, which are then used to update the user's dictionary and provide predictive text suggestions, allowing access to remote data stores and secondary user devices for text prediction, even when the information is not locally stored.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a dictionary stored in the device's memory is used for predictive text input, then text prediction can be performed, but the system lacks robust corpus of data for prediction especially when users need to input unique information such as passwords or codes
Solution Approach 1:
The patent transitions from local device storage to remote cloud-based storage by adding a network dimension. The system accesses a remote data store containing comprehensive corpus data including passwords, codes, and other unique information through network connections, thereby expanding data availability beyond local device constraints while maintaining prediction accuracy.
Solution Approach 2:
The patent introduces an image capture device as an intermediary between the user and the text input system. The device captures images of text (such as passwords or codes displayed on screens), extracts the text information, and uses it for prediction, thereby bridging the gap between visual information and text input without requiring manual entry.
2Ease of operation
If users manually re-enter unique information on other devices, then data can be accessed, but the process is arduous and time-consuming
Solution Approach 1:
The patent replaces the mechanical process of manual keyboard input with an optical system. The image capture device photographs text displayed on screens, and optical character recognition (OCR) technology automatically extracts and converts the visual text into digital text for prediction and input, eliminating the need for manual typing.
Solution Approach 2:
The system performs preliminary action by capturing and storing text information (such as passwords and codes) in the remote data store before they are needed. When the user needs to input this information on another device, the text is already available in the cloud, allowing instant retrieval and prediction without manual re-entry.
3Productivity
If limited input from the user is received for predictive text, then fewer characters need to be typed, but the prediction accuracy decreases when the input is insufficient
Solution Approach 1:
The patent implements feedback by continuously refining predictions based on additional context. When the user provides limited input, the system queries the remote data store for related text patterns and usage history, then uses this feedback information to improve prediction accuracy even with minimal user input, allowing fast typing without sacrificing precision.
Data Source
AI summary
A text prediction system and method for predicting entered text from a captured image is disclosed. An image capture device captures an image with within a field of view for the image capture device where the image has at least one object in the image. The image capture device identifies at least one object in the captured image. A set of words are identified for at least one object in the captured image. This set of words is then provided to a text entry device to be presented to the user as a possible suggestion.