AI Handwriting Recognition
Are you looking for a solution to digitize your handwritten documents. Easily store them, find information and categorize them? Easily digitize any handwritten document and recognize the handwritten text using JetStream with an accuracy over 95%. As well as the ability to extract any data and easily integrate or build workflows.
How to turn handwritten documents into digitized versions with interScan
From start to finish see how you can scan a handwritten document and how JetStream AI software will be able to reconigize the handwritten text, classify the document and extract any data needed from that document.
Step 1: Scanning the Document
In order to digitize a handwritten document you will first have to get it into an electronic format. The easiest and most efficient way to do this on a large scale is to use a production scanner to quickly scan large volumes of hand written documents.
Step 2: Recognizing, Converting & Storing Digitized Version
Once you have a scanned or digital version of the handwritten document. Then you can utilize JetStream Software, powered by machine learning to quickly recognize the handwritten text. JetStream is then also able to convert the handwritten text to a JSON output with machine printed text. Now you can store your handwritten text as a digitized fully machine interperted version.
Step 3: Classify & Extract Digitized Data
After having extracted the handwritten text and converted it to machine readable text, JetStream is also able to use a classification workflow to classify the document. The software also allows you to extract any data from the handwritten text, you can search for any keyword or term and find it within the digitized handwritten text.
Benefits of Digitizing Handwritten Documents with JetStream
>95%
Accuracy Handwritten
Documents
90%
Increased Automation
>80%
Cost Reduction
Recognize Handwriting
Get the latest technology in data capture through extraordinary accuracy in OCR and ICR, no matter the state of the document like for example distorted or low-quality scans, or difficult handwriting.
Automatic and Trained Classification
Efficiently and effectively categorize documents with JetStream, using trained models and workflows, going beyond regular rule-based or manual methods in terms of speed and efficiency.
Extract Specific Data
Using rule-free, few-shot learning technique Jetstream enables intelligent zonal data extraction. Allowing users to easily capture specific data fields and easily integrating with existing workflows.
Search & Find Handwritten Data
An exceptional solution in the realm of keyword spotting and handling extensive document collections including handwriting, historical scripts, or machine-print of subpar quality. Leveraging a patented technology, it ensures comprehensive keyword retrievability.
Model Training for Digitizing Handwritten Documents
With JetStream you have an easy to use dashboard which you can use to start creating and training your specific handwritten model based on test data that you provide. During training the software will allow you to use new data to test your model and see how it is performing.
Handwritten Digit Recognition
The use of advanced AI for recognizing handwritten digits transforms the way numerical data is processed, offering unparalleled accuracy even when dealing with varied writing styles or imperfect conditions. By understanding the context and structure of handwritten numbers, AI ensures that valuable numerical information, such as figures in forms or archival documents, is quickly converted into usable digital data, bridging the gap between manual records and automated systems.
JetStream in Action: Digitizing a Historical Handwritten Document
In this example you can see how a historical handwritten document is scanned and how the JetStream software is used to recognize the handwriting in the document and convert the handwriting to machine readable text. This text and the whole handwritten document can now be searched and manipulated.
Handwritten Text Recognition FAQ
What is HTR?
HTR, or Handwritten Text Recognition, is a technology that uses advanced algorithms to digitize and interpret handwritten text from physical documents, such as manuscripts, notes, or historical records. Unlike OCR (Optical Character Recognition), which focuses on printed text, HTR specializes in accurately reading and converting handwritten content into editable, searchable digital formats.
HTR is a critical tool for organizations involved in digital archiving, cultural heritage preservation, or data extraction from handwritten documents. It is particularly useful for enhancing accessibility and searchability of historical records, research papers, and government archives.
With the integration of HTR capabilities into modern scanners and our AI software, you can streamline your digitization workflows and ensure high accuracy in converting handwritten text to usable digital data.
What is the HTR process?
The Handwritten Text Recognition (HTR) process involves converting handwritten text from physical documents into digital, editable, and searchable formats. This process typically includes the following steps:
- Document Scanning: The handwritten document is scanned using high-quality scanners, such as the DeskPro or HiPro production scanners.
- Preprocessing: The scanned images are cleaned to enhance readability by reducing noise, correcting skewed text, and adjusting contrast. This ensures optimal conditions for the recognition software. This can also be done through our JetStream AI software.
- Text Recognition: Advanced HTR software analyzes the handwritten content using machine learning algorithms and pattern recognition techniques. Unlike OCR, which focuses on printed text, HTR interprets the variability of human handwriting with high accuracy.
- Post-Processing: Recognized text is refined using language models and dictionaries to correct errors, improving accuracy. This step helps ensure proper word formation and sentence structure.
- Output Generation: The processed text is converted into searchable and editable formats like PDF, TXT, or XML, enabling easier access and integration into digital archives or databases.
- Quality Assurance: The final output is reviewed for accuracy, and corrections are made manually if needed, ensuring the reliability of the digitized content.
The HTR process is essential for organizations digitizing handwritten records, historical documents, or forms, as it preserves valuable information while making it easily accessible for future use.