Intelligent Image Recognition
Enabling machines to accurately understand and classify scanned or digital document content

Meaning in documents is conveyed not only through text content, but also through visual structure reflected in layout, fonts, graphics, tables, diagrams, logos, and annotations. Though rules-based technologies assist machines in understanding document content, these approaches are often brittle when there are variations in the document collection.

PARC Solution & Approach

In contrast to the above approach, PARC researchers apply theories of perceptual document analysis – with computer vision techniques – to provide highly flexible, accurate document recognition and classification.

These techniques apply both to scanned paper documents and digital documents that may be difficult or impossible to parse (such as slide presentations and graphical web pages). Strengths of PARC's approach include:

• automatic document classification;
• text and graphics tagging;
• data extraction

...all of which reduce  the need for manual operators in document processing.

Example: ScanScribe

One example of PARC’s work in intelligent image recognition is "ScanScribe" – a perceptual-based document image editor that offers:
-	intelligent grouping;
-	selection; and
-	editing of graphical objects in sketches and whiteboard diagram images.

Download the ScanScribe™ Image Editor