Automatic Document Recognition

GdPicture’s Automatic Document Recognition ADR™ is a clever engine designed for automatic document classification and categorization tasks in a document and information management system. It allows your applications to identify invoices, checks, forms, orders, delivery notes, page separators or any kind of structured document.
It can also be used to develop image comparison applications.
GdPicture ADR™ technology delivers a wide range of document recognition functions that can be integrated into a variety of applications including: scanning, archiving, indexing, sorting, classification, search, document and information management.
You can automatically or manually assign an electronic document to one or more categories, based on its contents. The result is less document preparation and faster processes.

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GdPicture.NET ADR™: Automatic Document Recognition Engine

Examples of Usage

Simple application showing how to create templates, assigning documents to templates and then process document identification
Scan multiple documents at once using separator sheets
Comparison of two images

How to Use the Automatic Document Recognition Engine?

Download and install GdPicture.NET package from here.

You will find some compiled demo applications in
[Install directory]\Samples\Bin\
You will find C# and VB.NET demo applications including source code in
[Install directory]\Samples\WinForm\
You will find other code snippets within the online reference guide found here

GdPicture.NET Guides
You can find some discussions about GdPicture ADR engine in the dedicated section of our community forums located here

Automatic Document Recognition :: GdPicture ADR™

FAQs

GDPicture utilizes advanced AI algorithms to analyze and interpret diverse document formats, including invoices, checks, forms, orders, and delivery notes. Our SDKs can identify and classify structured documents by recognizing specific patterns and layouts, enabling accurate categorization and processing.

OCR is a fundamental component of Automatic Document Recognition, responsible for converting scanned images or PDFs into machine-readable text. By integrating OCR with AI technologies, GDPicture can accurately extract textual content from documents, even when dealing with complex layouts or varying fonts. This integration enhances the precision of data extraction and reduces manual intervention.

Yes, our technology is equipped with capabilities to recognize and process handwritten text and non-standard fonts. By employing machine learning models trained on diverse handwriting samples and font styles, these systems can accurately interpret and extract information from such documents, ensuring comprehensive data capture.

We employ a combination of AI-driven validation mechanisms and contextual analysis to ensure data accuracy. By understanding the context in which data appears and cross-verifying extracted information with predefined templates or databases, our library minimizes errors and enhance the reliability of the extracted data.

Our SDKs are versatile and can handle a wide range of documents, including but not limited to invoices, checks, forms, orders, delivery notes, and page separators. They are designed to identify and classify any structured document, facilitating efficient document management and workflow automation.

Our SDKs are designed with integration capabilities that allow seamless incorporation into existing business processes. They can export extracted data into various formats compatible with enterprise systems, enabling automated data flow from document capture to processing and storage, thereby enhancing operational efficiency.

Security is a critical aspect for all our clients so we take that very seriously. These SDKs implement robust protocols to protect sensitive information during processing and storage. Measures may include data encryption, access controls, and compliance with industry standards to ensure that confidential information is safeguarded against unauthorized access.

Yes, our SDKs are capable of processing documents in multiple languages. By supporting a wide range of languages, these systems can accurately extract and interpret data from documents written in different linguistic contexts, making them suitable for global applications.