145 lines
4.2 KiB
Markdown
145 lines
4.2 KiB
Markdown
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# About this Project
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This project is being developed as a practical part of bachelor's thesis at Brno Universtiy of Technology - Faculty of Information Studies. It is as of now a work in progress, no results guaranteed.
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The topic of this thesis is Generating a 3D Fingerprint Model. This application can be used to apply series of image processing filters to a fingerprint image to make it more suitable for conversion to 3D stl model and printing.
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It also includes the functionality to use generated image as a height map for generating an stl model.
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This model can either be planar or curved.
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# Prerequisites
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For now this is only viable for ubuntu gnu/linux machines
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Before cloning repository, you need these to succesfully use the application.
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* python version 3.10 is a requirement might work on earlier python 3 versions
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```sh
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apt install python3.10
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```
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* python graphical modules
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```sh
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pip install numpy==1.23.3 matplotlib==3.5.3 opencv-python=4.7.0.72
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stl==0.0.3 scikit-image==0.19.3
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```
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# Installation
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Installation is relatively fast and easy.
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1. Clone the repository
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```sh
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git clone ssh://git@strade.fit.vutbr.cz:3022/xlanro00/BP_DP-xlanro00.git
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```
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2. Prepare an image file containing fingerprint
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3. Run the application
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# Usage
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There are two ways to enter filters
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* manually from command line, list filter names and parameters
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```sh
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python src/main.py res/test_fp.png res/test_fp_cpy.png 100 denoise_tv_chambolle iterations=1 weight=0.1 median ksize=3
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```
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* manually from preset saved in a json config file, that can be used to create new presets
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```sh
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python src/main.py res/test_fp.png res/test_fp_cpy.png 100 --config config/config.json weak
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```
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# Configuration
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There is an option to input the filter series as a preset to json configuration file.
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```diff
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{
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"weak": [
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{
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"name": "denoise_tv_chambolle",
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"sigmaColor": 0.1,
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"weight": 0.01,
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"sigmaSpace": 3,
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"channelAxis": 0,
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"iterations": 1
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},
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{
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"name": "median",
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"ksize": 3
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},
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],
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"strong": [
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...
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]
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...
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}
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```
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All the filters used and their parameters will be described in documentation.
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# Comparison
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Image before processing the fingerprint and after applying a presets.
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<table>
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<thead>
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<th>Before</th>
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<th>After</th>
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</thead>
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<tbody>
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<td><img src="res/examples_git/example-before.png?raw=true" width="400" /></td>
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<td><img src="res/examples_git/example-after.png?raw=true" width="400" /></td>
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</tbody>
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</table>
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# Generating STL file
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It is possible to generate 3D printable stl planar model using `--stl` switch, which requires aditional parameter containing stl filename. Using `-p` switch makes the model planar. This is not the main goal of the application.
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Additional parameters with model thickness and papilar lines height will be optional.
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* Example stl generation
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```sh
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python src/main.py res/test_fp.png res/test_fp_mod.png 508 --config config/config.json weak --stl res/test_fp.stl -p
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```
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# Generating STL finger model
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When `--stl` switch is given without `-p`, the output model will either be a generated curved finger model, or later (if implemented) a fingerprint mapped to finger model.
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# Mapping to existing finger model
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This section will be added later.
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# Roadmap
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- [x] Load and store image
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- [x] Apply basic image processing filters
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- [X] Scale the image using given dpi
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- [X] Create filter library with more filters
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- [X] Add more suitable filters to the library
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- [x] Use presets from config files
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- [ ] Add the option to save current filter preset to config file
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- [X] Add the option to modify filter parameters
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- [X] Convert the processed image to stl lithophane
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- [ ] Add the option to curve the lithophane into the shape of a finger
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- [ ] Add the option to map the lithophane on a given finger model
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- [ ] Export final model ready for 3D print
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#
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### Author
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Rostislav Lán - xlanro00@stud.fit.vutbr.cz
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### Supervisor
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Ing. Petr Malaník
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### Links
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Project Link: [https://strade.fit.vutbr.cz/git/xlanro00/BP_DP-xlanro00](https://strade.fit.vutbr.cz/git/xlanro00/BP_DP-xlanro00)
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