提取图像的轮廓位置和方向

Question

I'm basically following a paper, " Using a statistical language model to improve the performance of an HMM-based cursive handwriting recognition system".

Here the author has extracted a vector of 9 features from each sliding window. quoting the paper:

The first three features are the weight of the window, its centre of gravity and the second order moment of the window.

Features four and five define the position of the upper and lower contour in the window, features six and seven give the orientation of the upper and lower contour by the gradient of the contour at the windows position, feature eight gives the number of black to white transitions in vertical direction, while feature nine gives the number of black pixels between the upper and lower contour.

I managed to calculate the first three features the paper is talking about, but I seem to have trouble understanding the features 4,5,6,7,8.

I can calculate the contour of an image. Suppose, this is a window of one of the text lines(windows is of length 14 pixels, as suggested by paper):

And this is the extracted contour of the image:

So what exactly is the upper and lower contour here? from where can I consider the limits, if it refers to the top and bottom pixels then I could have extracted those without contour extraction? Similarly the orientation of these contours is equally confusing.

I would really appreciate some guidance here.

Answer 1

I gave a look at the paper, and I am pretty sure that "upper" and "lower" should be read as "uppest" and "lowest". This especially makes sense as the authors have a special focus on the preprocessing of their data that they normalize in both the horizontal and vertical directions. They take care to have a kind of robustness to scale, writing angle,...

I guess that features 4 and 5 can be the extremal ordinates of the contours, which, combined with features 6 & 7 which are the gradients = orientations, give a good idea of the shape of these parts of the contour.

Feature 9, will be mostly useful to make the difference between letters that can have similar vertical shapes I guess, such as "i", "l", "j".

This is my understanding. Hope this helps!