Preprocessing

Fingerprint preprocessing module for DBOX

Dependencies:

The mentioned or newer versions are recommended

Getting Started:

You need to provide valid paths to these libraries and their header files in .pro file.
Build and run the project to generate .so (.dll / .lib) files
Include the library and header files to your own application
Copy the 'core' folder to your root project directory

API

Required

int loadInput(cv::Mat imgOriginal);
int loadInput(QVector<cv::Mat> imgOriginals);
int loadInput(QString inputPath);
  
void start();

Usage:

First you have to load input, which can be:

cv::Mat image
QVector of cv::Mat images
Image input path for a .jpg, .png, .bmp, .tif file
Image input directory

Just call start()

Optional

void setPreprocessingParams(int blockSize = 13, double gaborLambda = 9, double gaborSigma = 3, int gaussBlockBasic = 1, double gaussSigmaBasic = 1.0, int gaussBlockAdvanced = 121, double gaussSigmaAdvanced = 10.0, int holeSize = 20);  
  
void setFeatures(bool useAdvancedMode, bool useContrastEnhancement = true, bool useAdvancedOrientationMap = true, bool useHoleRemover = true, bool generateInvertedSceleton = true, bool useQualityMap = true, bool useMask = false, bool useFrequencyMap = false);  

void setCPUOnly(bool enabled, int numThreads = 0);  
  
void setMaskParams(CAFFE_FILES maskFiles, int blockSize, int exBlockSize, bool useSmooth);  
  
void setFrequencyMapParams(CAFFE_FILES freqFiles, int blockSize, int exBlockSize);

Usage:

With setPreprocessingParams(...) you can set the must important parameters required for image processing, the default parameters are recommended for 500dpi images
With setFeatures(...) you can set some optional features which can affect the output image quality, the advanceMode gives you all the intermediate results generated during preprocessing
With setCPUOnly(...) you can force the library to use only CPU for image processing (notice: it can be slower than GPU) and set the number of CPU threads you want to use for image processing in defined phases (notice: numThreads = 0 means automatic ideal thread number)
With setMaskParams(...) and setFrequencyMapParams(...) you can set the Caffe model files and parameteres required for classification with neural network to generate mask or frequency map for the input image

SIGNALS:

preprocessingDoneSignal(PREPROCESSING_ALL_RESULTS results);  
  
preprocessingDoneSignal(PREPROCESSING_RESULTS results);  
  
preprocessingSequenceDoneSignal(QMap<QString, PREPROCESSING_ALL_RESULTS> results);  
  
preprocessingSequenceDoneSignal(QMap<QString, PREPROCESSING_RESULTS> results);
  
preprocessingDurationSignal(PREPROCESSING_DURATIONS durations);  
  
preprocessingErrorSignal(int errorcode);

Important notice:

If you load an image or an image path
- You get preprocessingDoneSignal with PREPROCESSING_ALL_RESULTS if the advancedMode is enabled
- You get preprocessingDoneSignal with PREPROCESSING_RESULTS if the advancedMode is disabled
If you load a vector with images or an input directory
- You get preprocessingSequenceDoneSignal with PREPROCESSING_ALL_RESULTS if the advancedMode is enabled
- You get preprocessingSequenceDoneSignal with PREPROCESSING_RESULTS if advancedMode is disabled
You get preprocessingDurationSignal with duration values in ms for each phase during preprocessing if it's finished successfully
You get preprocessingErrorSignal with the error code if an error occured during preprocessing

A simple example how to use signals in your application
yourclass.h:

#include "preprocessing.h"

class YourClass: public QObject
{
    Q_OBJECT  
  
private:  
    Preprocessing p;  
    
private slots:
    void proprocessingResultsSlot(PREPROCESSING_RESULTS result);
}

yourclass.cpp:

#include "yourclass.h"
YourClass::YourClass()
{
    qRegisterMetaType<PREPROCESSING_RESULTS >("PREPROCESSING_RESULTS");
    connect(&p, SIGNAL(preprocessingDoneSignal(PREPROCESSING_RESULTS)), this, SLOT(proprocessingResultsSlot(PREPROCESSING_RESULTS)));
}

void YourClass::proprocessingResultsSlot(PREPROCESSING_RESULTS result)
{
    cv::imshow("Fingerprint Skeleton", result.imgSkeleton);
}

For more please visit Qt Signals & Slots.

stupel/Preprocessing

Preprocessing

API