I was going through the project lists of Andrew NG from his stanford machine learning course and I found a project based on recreation of calligraphic characters. To do so firstly we need to extract strokes from characters and I can only understand it in
bits and pieces and I cannot understand at all how to implement it in matlab. This is the link to the report.
http://cs229.stanford.edu/proj2016/report/GuoTaoZheng-Createyourowncalligraphyartwork-report.pdf
I also read the research paper that the stroke extraction method is based on.But I did not understand that too like there were some terms that I could not understand. And not to mention I can't understand just how to implment all tge pixel related
operations mentioned.I am a beginner in image processing. SO please any help is appreciated.
Quoting some lines from the paper.Here is the link to it.
https://pdfs.semanticscholar.org/3d01/7f671c6bb9d65e982d389ec7e64192670154.pdf?_ga=2.19812592.939050488.1498745883-660081635.1498745883
We use the direction contribution of the segments to
estimate the degree for each pixel on the thick-line image.
Given a binary image, for each black pixel p(r,c), let
Dk(r,c) denote the orientation distance between the pixel
and the boundary point along the kth quantized
orientation, where k = 1, 2, …, M, and M is an integer that
denotes the quantization number from 0o
to 360o
. The
orientation distance is called point-to-boundary
orientation distance (PBOD).
The distribution of the PBODs contains information
about the degree of each pixel. We can easily tell that the
PBODs along the quantized orientations of the branches
are much larger than that along other quantized
orientation. So, to estimate the degree of each pixel, we
need only calculate the number of the crests of the
distribution of all the PBODs of the pixel. Figure 2 shows
some cases of the distribution. The resolution of
quantization is 3degrees.
What is quantisation and orientation distance and how to implement these in matlab?
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