Rostislav Lán
2 years ago
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# User Manual for fingerprint image filtering and model generating application
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## Introduction
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This project has been developed as a part of bachelor's thesis at Brno University of Technology - Faculty of Information Technology.
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The topic of this thesis was Generating a 3D Fingerprint Model from input fingerprint image.
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This application consists of two main parts.The first part of the application uses image filters to enhance fingerprint images.
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Application also implements a custom filter library, which consists of several filters imported from image processing modules.
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The second part uses the processed image to make a 3D model of the fingerprint.
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The model can then be used to print an accurate representation of human fingerprint using a 3D printer.
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## Getting started
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The application has only been tested on Ubuntu gnu/linux machines.
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It should however be possible to use it in on most linux distributions, WSLs and also virtual machines of most linux distributions.
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To start off, 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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```
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sudo apt install python3.10
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```
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* **virtualenv** package for virtual enviroment creation, other packages are installed automatically later:
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```
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pip install virtualenv
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```
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## Installation
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This will install the application and its components into the Documents directory.
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It will also install several required python packages, including venv, which is used to create a virtual enviroment.
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1. Go to a suitable installation folder, for example **Documents**:
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```
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cd /home/username/Documents
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```
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2. Clone the repository to a suitable directory, for example:
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```
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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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3. Go inside cloned directory:
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```
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cd BP_DP-xlanro00
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```
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4. Create and enter the virtual enviroment:
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```
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virtualenv .venv && source .venv/bin/activate
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```
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5. Install required python modules from **requirements.txt**:
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```
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pip install -r requirements.txt
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```
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6. Now, you are all set to run the application.
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Examples of how to do this are listedin the section bellow.
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# Filtering images
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Once all the requirements are installed, the application is ready to use.
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Fingerprint sample is located in res/examples, its name is Palec_P4.tif.
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* You will need to enter the virtual enviroment every time you want to use the application.
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```
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source .venv/bin/activate
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```
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* The application requires **input** and **output filenames** including path from the root project directory, **dpi** and **filter list** as shown bellow.
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```
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python3 src/main.py input_file output_file dpi filters
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```
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There are two ways to enter the filters:
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1. manually list all filter names and their parameters on the **command line**:
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```
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python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_cline.png 600 total_variation weight=0.15 median ksize=5
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```
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2. load them from preset in a JSON **configuration file**, that can be used to tune and modify existing presets, or create new ones:
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```
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python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_preset.png 600 --config conf/conf.json git_example
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```
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## Configuration and presets
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#
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There is an option to input the filter series as a preset from JSON configuration file.
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Here the presets are stored and are ready to be used whenever needed. You can usehow many filters you need as long as you like the output.
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It is therefore highly recommended to check the output after every preset change.
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Filter used in the example above is listed bellow, along with the general form of configuration file.
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<style>
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table {
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border-collapse: collapse;
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width: 100%;
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}
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th, td {
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padding: 8px;
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text-align: left;
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border-bottom: 1px solid #ddd;
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}
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th {
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background-color: #f2f2f2;
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}
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.code {
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font-family: 'Courier New', monospace;
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background-color: #f5f5f5;
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padding: 8px;
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}
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.language-json {
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color: #333;
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}
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</style>
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<table>
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<thead>
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<tr>
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<th>General format</th>
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<th>Woking example</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>
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<pre><code class="language-json">
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{
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"preset": [
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{
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"name": "filter_name",
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"parameter": value,
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"parameter": value
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},
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{
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"name": "filter_name",
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"parameter": value
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}
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],
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"preset": [
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...
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]
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...
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}
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</code></pre>
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</td>
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<td>
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<pre><code class="language-json">
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{
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"git_example": [
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{
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"name": "denoise_tv_chambolle",
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"weight": 0.01,
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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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}
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</code></pre>
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</td>
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</tr>
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</tbody>
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</table>
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To avoid accidental loss of information caused by modifying presets that have been used to generate stl files,
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these presets are stored inside a JSON file db.json.
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This file serves as a simple database for storing presets, stored presets are modified by adding generated hash of all the filters in that preset.
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There is also an option to save current command line setting as a preset using -d switch and it's new name:
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## Available filters with parameters
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#
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Overview of all implemented filters and their parameters with descriptions is listed below.
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- median blur
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- ksize (int) - Kernel size, determines how large of an area the filter processes.
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- gaussian blur
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- sigma (int) - Gaussian kernel standart deviation, determines the weight of further pixels on the currently processed pixel.
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- bilateral blur
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- diameter (int) - Diameter of pixel neighborhood used for filtering.
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- sigmaColor (int) - Determines the weight of pixels of different color.
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- sigmaSpace (int) - Determines the weight of further pixels.
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- bilateral_scikit
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- sigmaColor (float) - Determines the weight of pixels of different color.
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- sigmaSpace (float) - Determines the weight of further pixels.
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- nlmeans (non-local means)
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- patch_size (int) - Size of patches used for denoising.
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- patch_distance (int) - Distance in pixels where to search for patches.
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- h (float) - Cut-off distance, higher means more smoothed image.
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- total_variation
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- weight (float) - Denoising weight, determines how much the image will be denoised.
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- block_match
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- sigma (float)- Standart deviation
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- unsharp mask scikit
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- radius (int) - Radius of the gaussian filter.
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- amount (float) - Strength of the unsharp mask, determines how much of the mask will be used for filtering.
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- farid
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- meijering
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- sato
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- hessian
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- sigmas (float) - Standart deviations
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- invert
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- scale_values
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- binarize
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- threshold (int) - Value to cut differentiate pixels.
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- binarize_otsu
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- add_margin
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- margin (int) - Number of pixels to add to the sides of the image.
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- color (int) - Color value of newly added pixels.
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- erode
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- kernel (numpy matrix) - Shape of the kernel used to erode image.
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- dilate
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- kernel (numpy matrix)- Shape of the kernel used to dilate image.
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# Generating fingerprint model
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## Generating curved finger model
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It is possible to generate stl model using the `--stl` switch. This requires more parameters, first of which is the type of generated fingerprint.
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If the mode is set to `c`, the output model will be a curved finger model, with optional parameters following the filename controlling its shape.
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First optional parameter is papilar line height `height_line`, second is thickness of the model `height_base`,
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third the rate of curvature along x axis `curv_rate_x` and the third is the rate of curvature along y axis `curv_rate_y`.
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* General form for curved stl generation:
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```
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python3 src/main.py input_file output_file dpi --config config_file preset --stl c height_line height_base curvature_x curvature_y
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```
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* Working example curved stl generation:
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```
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python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_preset.png 600 --config config/config.json git_example --stl c 2 10 2 2
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```
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## Generating planar finger model
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Using `p` mode makes the generated fingerprint model flat.
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Optional parameters are height of the papilar lines and base thickness.
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* General command form for planar stl generation:
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```
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python3 src/main.py input_file output_file dpi --config config_file preset --stl p height_line height_base
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```
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* Working example of planar stl generation:
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```
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python3 src/main.py res/examples/Palec_P4.tif res/examples/Palec_P4_from_preset.png 600 --config config/config.json git_example --stl p 2 10
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```
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## Mapping to existing finger model
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This section will be added later, (if implemented) mapping of fingerprint to a given finger model.
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* General command form for mapped stl generation:
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```
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python3 src/main.py input_file output_file dpi --config config_file preset --stl m height_line height_base finger_file
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```
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# Usage
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When in doubt, you can always check the help with:
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python3 src/main.py --help
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Which will print out the following message.
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```
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usage: main.py [-h] [-m | --mirror | --no-mirror] input_file
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output_file dpi ([-c | --config config_file preset] |
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[filters ...]) [-s | --stl_file p height_line height_base |
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--stl_file c height_line height_base curv_rate_x curv_rate_y |
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--stl_file m height_line height_base finger_file]
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Program for processing a 2D image into 3D fingerprint.
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positional arguments:
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input_file input file path
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output_file output file path
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dpi dpi of used scanner
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filters list of filter names and their parameters in form
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[filter_name1 param1=value
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param2=value filter_name2 param1=value...]
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options:
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-h, --help show this help message and exit
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-m, --mirror, --no-mirror
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switch to mirror input image
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-s [STL_FILE ...], --stl_file [STL_FILE ...]
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create stl model from processed image
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-c CONFIG CONFIG, --config CONFIG CONFIG
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pair: name of the config file with presets,
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name of the preset
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```
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# Troubleshooting
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<table>
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<thead>
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<tr>
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<th>Error message</th>
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<th>Solution</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>
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main.py: error: the following arguments are required: input_file, output_file, dpi, filters
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</td>
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<td>
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You probably forgot to include some of the required arguments.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Input file res/Palec_P14.tif does not exist
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</td>
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<td>
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The file you want to process does not exist, check the filename again.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Config file not found
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</td>
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<td>
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The config file you want to load config from does not exist, check the filename again.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Preset not found in config file
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</td>
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<td>
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The preset is not present in selected config file, check the file again or select the correct config file.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Filter undefined_filter not found
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</td>
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<td>
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One of the filters from command line is not defined in the library, check its name.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Unrecognized generation mode
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</td>
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<td>
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The first parameter of stl generation should be p, c or m, check it again.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Line depth must be less than plate thickness
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</td>
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<td>
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When generating a cast, the depth must be less than the base plate thckness, otherwise it would have holes on the other side.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Depth of plate height must be positive
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</td>
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<td>
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Cannot generate negative base plate thickness, check order of arguments.
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</td>
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</tr>
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<tr>
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<td>
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ERROR: Base and line height must both be positive
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</td>
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<td>
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In curved generation any negative argument is an error, casts are only for planar mode.
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</td>
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</tr>
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</tbody>
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</table>
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Loading…
Reference in new issue