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Creating Text Segmentation Models

The graphical editor for text segmentation performs two operations:

  1. Thresholding an image with one of several different methods to get a single foreground region corresponding to all characters.
  2. Splitting the foreground region into an array of regions corresponding to individual characters.

Details about using OCR filters can be found in Machine Vision Guide: Optical Character Recognition.

To configure text extraction please perform the following steps:

  1. Add an ExtractText filter to the program.

  2. Set the region of interest on the inRoi input. This step is necessary before performing next steps. The image below shows how the ROI was selected in an example application:

  3. Click on the "..." button at the inSegmentationModel input to enter the graphical editor.

  4. When entering first time, complete the quick setup by selecting most common settings. In this example a black non-continuous text should be extracted from a uniform background. Configuration was set to meet these requirements.

  5. After the quick setup the graphical editor starts with some parameter set. Adjust the pre-configured parameters to get best results.

  6. Configure a character extraction algorithm. In this case thresholding value is too high and must be reduced.

  7. Select a character segmentation algorithm.

  8. Set the minimal and the maximal size of a character. The editor shows the character dimensions when the character is selected in the list below.

  9. Select a character sorting order, character deskewing (shearing) and image dilation.

  10. Check results using available images.

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