What kind of features that can be extracted from binary image

edit

It's more an addition to Stevens answer:

• Histogram based features are e.g. HOG features, or Histograms of LBPs.
• Profile features are computed from the outer boundary of your letter / word in a specific direction, e.g. left profile: go from the left bounding box border to the right until you hit your first pixel and do this for each row (thus a proper binarization is important) and you'll get a left profile. You can do the same for the other directions too (top to bottom, bottom to top, left to right, right to left). From these profiles you can then compute several statistics (mean, std-dev., etc.).

A link to color histogram matching :

http://facweb.cs.depaul.edu/research/techreports/tr06-010.pdf

About image profile, guess they are talking about interesting keypoints to detect in the image or about the gradient image. Information can be found on the following links:

• http://docs.opencv.org/doc/tutorials/features2d/feature_detection/feature_detection.html#feature-detection

• http://docs.opencv.org/doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.html#sobel-derivatives

Altough remember that feature point extractors do not work well with binary images. They need more information to find enough points.