Tristan-cs488-tasks

From Earlham CS Department
Revision as of 16:01, 28 November 2012 by Twright09 (talk | contribs) (added note page)
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Set of discrete tasks for Schrift (the name of the proposed handwriting recognizer). These notes and more are are kept on paper. Strikethrough tasks are done or no longer necessary, hopefully dated entries will make it clear which. This page might get a little messy.

I have a digital note page which I access and edit relatively frequently, it can be viewed here.

  • File structuring
    • just doing it, will restructure later.
  • Image importing
    • Read in jpg image
  • Text Scan
    • OpenCV image import, test threshold filter
    • Algorithm for figuring out correct threshold value. Take a mean of the page color and adjust for that value. Usually 110±10?
    • Draw box around where dark is detected, extract that selection.


  • Line segmentation
    • Decided it was not necessary to find beginning and end of line
    • General Algorithm
      • Scan from top line by line
      • Stop when line of nothing
      • create selection between line1 and line2
      • push to dynamic array as line[0]
  • Word segmentation
    • Outline algorithm similar to line segmentation
  • Character segmentation
    • openCV historgram test
  • 11-26-12: I tried an openCV example that makes and highlights bounding box and bounding polygon regions, it gave me this image. Suddenly I'm on the recognition step??
  • 11-27-12: The vector that the contours are in are stored in an unusual order, if I sort them by the rectangles bottom left coordinate, a count of lines could be established and I could get the letters into their correct order. Once in order I can detect spaces easily by looking at changes between characters in the x direction. line and word segmentation are basically kaput, instead I have line and word detection.
  • Character recognition
    • Figure out a basic neural network
      • look atOpenCV neural network type
      • I've found some NN tutorials, the implementation of one is what's bothering me.