Handwritten Text Processing via Transparent Overlay
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Solution Overview
Problem
Current technologies face challenges in processing and enabling text processing functions on documents containing handwritten inputs, as they struggle to effectively differentiate and analyze handwritten text within mixed textual content, limiting the ability to perform tasks like search and automation in domains such as healthcare and finance.
Innovation Solution
A handwritten text processing system that converts digitized documents into binary images, segments them into patches, extracts features like convex hulls and Hu moments, and uses custom convolutional neural networks to identify and process both typed and handwritten text, allowing for transparent text overlay on images for user interaction and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If machine learning techniques such as neural networks are employed for analyzing handwritten inputs, then the ability to process handwritten text is improved, but the complexity of the processing system increases
Solution Approach 1:
The patent segments the document processing into distinct stages: image acquisition, binarization, feature extraction (convex hulls, Hu moments), and classification. This segmentation allows each stage to be optimized independently, reducing overall system complexity while maintaining high handwritten text analysis capability through specialized processing at each stage.
Solution Approach 2:
The patent introduces intermediate representations (binary images, convex hull features, Hu moment invariants) that serve as mediators between the raw handwritten input and the final classification. These intermediaries simplify the analysis by transforming complex handwriting variations into standardized geometric and statistical features that are easier to process.
2Measurement precision
If documents are converted into binary images and segmented into patches for feature extraction, then the precision of handwritten text identification is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary binarization and feature extraction (convex hulls, Hu moments) on the entire document before segmentation into patches. This preliminary action prepares the data in advance, allowing the subsequent patch-based classification to proceed more quickly while maintaining high precision through the use of pre-computed geometric and statistical features.
Solution Approach 2:
The patent extracts more features than strictly necessary (including both convex hulls and Hu moments) and processes patches at a finer granularity than the minimum required. This excessive action ensures high identification precision by capturing subtle handwriting characteristics, while the efficient computation of these features keeps processing time acceptable.
3Ease of operation
If transparent text overlay is used to maintain document appearance and enable user interaction, then the usability is improved, but the system complexity increases
Solution Approach 1:
The patent uses transparent text overlay with adjusted opacity and color properties to enable user interaction while preserving the original document appearance. This technique allows the system to maintain a simple interface structure by leveraging visual properties rather than requiring complex multi-layer display mechanisms.
Data Source
AI summary
A handwritten text processing system processes a digitized document including handwritten text input to generate an output version of the digitized document that allows users to execute text processing functions on the textual content of the digitized document. Each word of the digitized data is extracted by converting the digitized document into images, binarizing the images, and segmenting the images into binary image patches. Each binary image patch is further processed to identify if the word is machine-generated or if the word is handwritten. The output version is generated by combining underlying images of the pages of the digitized document with words from the pages superimposed in a transparent font at positions that coincide with the positions of the words in the underlying images.