Handwriting Recognition Retaining Original Strokes
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Solution Overview
Problem
Existing electronic writing systems lose the personal touch by converting handwritten strokes into font characters, failing to retain the original input strokes and the natural look of handwriting.
Innovation Solution
A handwriting recognition and processing system that recognizes and processes strokes by determining stroke and character boxes, margins, and correlations, allowing for manipulation and retention of original input strokes, and differentiating between stylus and touch inputs to provide a more personalized and natural handwriting experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If handwritten strokes are converted into font characters for electronic writing systems, then recognition accuracy and standardization are improved, but the natural look and personal touch of handwriting are lost
Solution Approach 1:
The system segments the handwritten input into individual strokes and groups them into character candidates, allowing each stroke to be preserved and analyzed separately while still enabling character recognition. This segmentation allows the system to maintain both the original stroke information and achieve recognition accuracy.
Solution Approach 2:
The system creates a digital copy of the original handwritten strokes that preserves the natural handwriting appearance while enabling computational processing. The original stroke data is retained and can be displayed or manipulated without losing the personal touch of the handwriting.
2Productivity
If pre-programmed stroke sequences are used to correspond to letters, then recognition speed is improved, but adaptability to different handwriting styles is reduced
Solution Approach 1:
The system dynamically adjusts the recognition process by evaluating multiple character candidates based on stroke groups and margins, rather than relying on fixed pre-programmed sequences. This dynamic approach allows the system to adapt to various handwriting styles while maintaining recognition speed through efficient processing algorithms.
Solution Approach 2:
The system changes parameters such as margin sizes and stroke groupings to adapt to different handwriting styles. By adjusting these parameters dynamically, the system can accommodate variations in handwriting while maintaining efficient recognition performance.
3Measurement precision
If stroke boxes and margins are provided around each stroke, then character recognition accuracy is improved, but computational complexity increases
Solution Approach 1:
The computational task is segmented into manageable steps: identifying individual strokes, creating stroke boxes, adding margins, grouping strokes into character candidates, and evaluating overlap. This segmentation reduces the overall computational complexity by breaking down the complex recognition task into simpler, more efficient sub-tasks.
Data Source
AI summary
The present disclosure relates to a method and system of processing original handwriting input, the system and method being capable of recognize a plurality of strokes provided on the input recognition interface, the method including: determining a stroke box around each stroke; determining overlap between the stroke boxes; correlating overlapping stroke boxes to one or more characters; providing a character box around each of the one or more characters; determining overlap between character boxes; correlating overlapping character boxes to one or more words; providing a word box around each of the one or more words; provide a word margin around each of the one or more word boxes; determining overlap between each word box to determine a line; wherein each of the characters, words, or lines can be individually selected and rearranged, the system automatically adjusting spacing or placement of surrounding elements to allow for the rearrangement.