This repository cointains all the material (presentation, code, etc...) I developed for the Signal, Image & Video course project.

In releases is available the final version of the slides. It is also available in the root as presentation.pdf

Please use Adobe Acrobat Reader, Adobe Acrobat DC, PDF-XChange, acroread, or Foxit Reader to open the slides since there are some animations and videos that other pdf readers cannot render.

Slide 12 "Hit-or-Miss-Trasform" contains a video. To be played, hit-or-miss.mp4 must be located in the same directory of presentation.pdf.

If you want to compile the slides yourself, you need a LaTex distribution with the necessary packages installed. A simple compilation with pdflatex should be enough to get the pdf.

In the root folder of this repo you can find the Jupyter notebook skeletonizion.ipynb in which the three algoritms presented in the slides are briefly described, implemented and compared.

In order to run it you need the following steps:

1. Have [email protected] installed in your machine.
2. Create a virtual environment python3 -m venv venv
3. Activate the virtual environment source venv/bin/activate
4. Execute pip3 install -r requirements.txt to install all necessary dependencies.
5. Start the jupyter server jupyter notebook
6. Enjoy!

Since the algorithms presented are parallel algorithms, in order to demonstrate it I implemented a C++ version of Zhang-Suen Algorithm that uses parallel programming techniques.

In the folder c++ there are three .cpp files:

• zhang.cpp containing a 1:1 translation from Python to C++ of the algorithm present in the jupyter notebook.
• zhang_optimized.cpp containing an optimized version of Zhang-Suen algorithm in C++.
• zhang_threads.cpp containing a parallelized version using C++ std::thread.

To run it you need to have installed OpenCV library and update CMakeLists.txt with your OpenCV installation path on line 12. To compile and run:

1. mkdir c++/build
2. cd c++/build
3. cmake .. to configure cmake.
4. make to compile.
5. ./<executable_name> to run.

I developed an animation to visualize Hit-or-Miss Transform in action using Manim library. The relative code is in hitmiss-animation folder.

If you want to re-render it yourserlf you need to install manim and follow the guide.

In the folder stepbystep_execution there are images representing the evolution of the skeleton state for each algorithm. There is a folder for each algorithm.

I used them to make animations available in each folder as <algorithm_name>.mp4.