Handwriting Recognition - Off-line Recognition - Character Recognition - Feature Extraction

Feature Extraction

Feature extraction works in a similar fashion to neural network recognizers however, programmers must manually determine the properties they feel are important.

Some example properties might be:

  • Aspect Ratio
  • Percent of pixels above horizontal half point
  • Percent of pixels to right of vertical half point
  • Number of strokes
  • Average distance from image center
  • Is reflected y axis
  • Is reflected x axis

This approach gives the recognizer more control over the properties used in identification. Yet any system using this approach requires substantially more development time than a neural network because the properties are not learned automatically.

Read more about this topic:  Handwriting Recognition, Off-line Recognition, Character Recognition

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