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Pre-recognition is the first stage of processing a semi-structured document. Unlike fixed documents, which are designed with computer processing in mind, unstructured documents vary in structure, and their data fields may be placed in different parts of the page. For this reason, pre-recognition is used to detect objects on the document that could signal the location of data fields. Since pre-recognition may take considerable time, FlexiLayout Studio allows you to run pre-recognition once, independently of FlexiLayout matching, so that you can concentrate entirely on creating and testing your FlexiLayout.

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Assess the quality of pre-recognition results

Assess the quality of the pre-recognition results before you start creating your FlexiLayout. The quality of pre-recognition depends on the quality of the test images in the batch. The quality of the test images, in turn, depends on the scanning parameters such as brightness, contrast, and resolution. If you are not satisfied with the quality of the pre-recognition results, you may need to change the scanning options and re-scan your test documents. Note also that FlexiLayout Studio allows you to add images scanned at different resolutions, so that you can experiment with pre-recognition and FlexiLayout matching and select the optimal scanning options.

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Pre-recognition modes

Pre-recognition can be run in fast or full mode. For more information, see Pre-recognition parameters. When a FlexiLayout is being developed, pre-recognition need not be perfect. There is always a way of finding practically any data field even if several recognition errors have been made. Indeed, sometimes pre-recognition speed is more important than quality. The quality of recognition may be tackled at a later stage in a data capture application, where you can specify data types for each field, thereby greatly improving the quality of recognition.

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Basic objects detected during pre-recognition

During pre-recognition, FlexiLayout Studio analyzes the locations of dots of various colors, detects basic objects, and merges text fragments into words and lines. The following types of basic objects are detected:
  • Text
  • Picture
  • Punctuation mark
  • Inverted text
  • Separator
  • Barcode
  • Checkmark
Once basic objects have been detected, the text objects are recognized. Recognized text can be viewed as one of the following two types:
  • Recognized Words
  • Recognized Lines