Don’t Have Drop Out Forms? Use Template Removal!

A great way to improve recognition results in general is to use a drop out form whenever possible.  These forms are printed with ink that can be “dropped out” by the scanner during image capture (usually red).  What you’re left with is a nice white page with nicely positioned data. Using drop out templates is […]

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Benefits of Addressee Name Recognition

A decade of intensive investment in Optical Character Recognition (OCR) systems have resulted in unparalleled success in the speeding up of mail sorting, the increase of OCR reading quality, and the reduction of manual data entry costs. This progress has made recognition technology the most important factor influencing the efficiency of mail sorting equipment. The […]

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Video: Intelligent Document Recognition | Benefits and Features

Want to learn more about document capture and only have a couple of minutes? Well, do we have the video for you! Intelligent Document Recognition (IDR) software allows companies to automate data capture and reduce manual data entry. Parascript’s FormXtra Capture provides the ability to process any document, with any data, from any source. It […]

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The 2 Most Common Misconceptions about Recognition Technology

When it comes to automated recognition technology, there are 2 common misconceptions about expected results that can be easily solved with tuning. Misconception #1: All items in a stream are equally hard to read, both automatically and manually The items that cause the most errors and rejects are not random. In fact, the items that […]

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The Truth about Trainable Forms Processing

There are many capture systems that market the ability to automatically “learn” document formats and layouts or to allow the system to be “trained”. In either case, the objective is twofold: Minimize the effort required to define document rules specific to each document variant and Improve overall recognition rates and lower error rates. The Problem […]

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Understanding Recognition: Reject Mechanism

Let’s explore the mathematical model for optimizing the tradeoff between errors and rejects. The reject mechanism helps to guarantee the specified error level required by an application. Recognition engines usually return an answer accompanied by a value parameter called confidence value. The confidence value ranges from 0 to 100 and indicates how confident the engine is that […]

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Understanding Recognition: Errors and Rejects

There are 3 possible outcomes when recognition engines attempt to read any data: the correct answer, error, or reject. This post will focus on understanding errors and rejects and how to find the right balance between them. Errors refer to the instances when a recognition engine gives an incorrect result. The problem with errors is […]

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Operating Point – The Most Critical Number in Recognition

There’s a lot of confusion around how to judge the accuracy of intelligent character recognition (ICR). Creating a metric is critical, as it helps us define the business case. To that end, Parascript engines produce an internal metric, called “confidence value”. And while this metric is critical to defining the business case, it is really […]

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