OCR (Concept)

OCR stands for Optical Character Recognition. It allows text from paper documents to be digitized to be searched or edited by other software applications. OCR converts typed or printed text from digital images of physical documents into machine-readable, encoded text. This conversion allows Grooper to search text characters from the image, providing the capability to separate images into documents, classify them and extract data from them.

About

The general process of OCR'ing a document is as follows in Grooper:

1) The document image is handed to the Recognize activity, which references an OCR Profile, containing the settings to perform the OCR operation.

2) The OCR Engine (set on the OCR Profile) converts the pixels on the image into machine readable text for the full page.

3) Grooper reprocesses the OCR Engine's results and runs additional OCR passes using the OCR Profile's Synthesis properties.

4) The raw OCR results from the OCR Engine and Grooper's Synthesis results are combined into a single text flow.

5) Undesirable results can be filtered out using Grooper's Results Filtering options.

What is an OCR Engine?

OCR Engines are software applications that perform the actual recognition of characters on images, analyzing the pixels on the image and figuring out what text characters they match.

OCR Engines themselves have three phases:

Pre-Processing

First and foremost, all OCR applications require a black and white image in order to determine what pixels on a page are text. This is done by a process called "thresholding" which determines a middle point between light pixels and dark pixels on the page. Lighter pixels are then turned into white and darker ones are turned into black pixels. You are left with only black and white pixels, with (ideally) all text in black and everything else faded into a white background. Some OCR Engines also contain de-skewing, despeckling, line removal, aspect ratio normalization, or other pre-processing functions to improve OCR results.

FYI

Grooper has it's own pre-processing capabilities through its Image Processing operations. OCR Engines typically place these pre-processing functions in a "black box" for users. At best, the OCR Engine may allow you to turn the property "on" or "off" but may not allow you to configure it further to fine tune its results. Custom Image Processing can be performed using IP Profiles made of highly configurable IP Commands.

Character Recognition

There are two basic types of recognition algorithms: matrix matching and feature extraction.

Matrix matching compares a NxN matrix of pixels on a page to a set of stored character glyphs. This is also known as "pattern recognition" or "image correlation".

There are a number of issues with this approach. First, the glyph must be isolated from the rest of the image. You will encounter OCR errors

• Post-Processing