将开源虹膜识别算法OSIRIS4.1移植到Windows

开源虹膜识别算法OSIRIS是在Linux下运行的，为了介绍给众多windows平台下的开发者，这里简述一下如何把它移植到windows。

开发平台Windows XP + Visual Studio 2008 + OpenCV2.3.1。

1.新建一个对话框工程，将OSIRIS源码中的如下文件拷贝过去并添加到工程：

OsiCircle.cpp/.h
OsiEye.cpp/.h
OsiManager.cpp/.h
OsiProcessings.cpp/.h
OsiStringUtils.h

2.在上述源码中，只需要对OsiManager.cpp/.h做少量修改即可使用了：

OsiManager.cpp

#include <fstream>
#include <iterator>
#include <stdexcept>
#include "OsiManager.h"
#include "OsiStringUtils.h"

using namespace std ;

namespace osiris
{
    OsiManager::OsiManager ( )
    {
        initConfiguration() ;   

	loadGaborFilters() ;
	loadApplicationPoints() ;
    }

    OsiManager::~OsiManager ( )
    {
        if ( mpApplicationPoints )
        {
            cvReleaseMat(&mpApplicationPoints) ;
        }
        
        for ( int f = 0 ; f < mGaborFilters.size() ; f++ )
        {
            cvReleaseMat(&mGaborFilters[f]) ;
        }
    }

    void OsiManager::initConfiguration ( )
    {
        // Options of processing
        mProcessSegmentation = false ;
        mProcessNormalization = false ;
        mProcessEncoding = false ;
        mProcessMatching = false ;
        mUseMask = true ;

        // Inputs
        mListOfImages.clear() ;
        mFilenameListOfImages = "" ;
        mInputDirOriginalImages = "./SourceImage/" ;
        mInputDirMasks = "" ;
        mInputDirParameters = "" ;
        mInputDirNormalizedImages = "" ;
        mInputDirNormalizedMasks = "./NormalizedMasks/" ;
        mInputDirIrisCodes = "./IrisCodes/" ;

        // Outputs
        mOutputDirSegmentedImages = "./SegmentedImages/" ;
        mOutputDirParameters = "./CircleParameters/" ;
        mOutputDirMasks = "./Masks/" ;
        mOutputDirNormalizedImages = "./NormalizedImages/" ;
        mOutputDirNormalizedMasks = "./NormalizedMasks/" ;
        mOutputDirIrisCodes = "./IrisCodes/" ;
        mOutputFileMatchingScores = "" ;

        // Parameters
        mMinPupilDiameter = 50 ;
        mMaxPupilDiameter = 160 ;
        mMinIrisDiameter = 160 ;
        mMaxIrisDiameter = 280 ;
        mWidthOfNormalizedIris = 512 ;
        mHeightOfNormalizedIris = 64 ;
        mFilenameGaborFilters = "./filters.txt" ;
        mFilenameApplicationPoints = "./points.txt" ;
        mGaborFilters.clear() ;
        mpApplicationPoints = 0 ;

        // Suffix for filenames
        mSuffixSegmentedImages = "_segm.bmp" ;
        mSuffixParameters = "_para.txt" ;
        mSuffixMasks = "_mask.bmp" ;
        mSuffixNormalizedImages = "_imno.bmp" ;
        mSuffixNormalizedMasks = "_mano.bmp" ;
        mSuffixIrisCodes = "_code.bmp" ;
    }

    void OsiManager::loadGaborFilters ( )
    {
	//不修改
    }

    void OsiManager::loadApplicationPoints ( )
    {
	//不修改
    }

	int OsiManager::processEye ( const string & rFileName , OsiEye & rEye )
	{
		// Strings handle
		OsiStringUtils osu ;
		// Get eye name
		string short_name = osu.extractFileName(rFileName);
		rEye.loadOriginalImage(mInputDirOriginalImages+rFileName); 
	
		/////////////////////////////////////////////////////////////////
		// SEGMENTATION : process, load
		 rEye.segment(mMinIrisDiameter,mMinPupilDiameter,mMaxIrisDiameter,mMaxPupilDiameter) ;
		// Save segmented image
		rEye.saveSegmentedImage(mOutputDirSegmentedImages+short_name+mSuffixSegmentedImages) ;

		/////////////////////////////////////////////////////////////////
		// NORMALIZATION : process, load
		rEye.normalize(mWidthOfNormalizedIris,mHeightOfNormalizedIris) ;

		/////////////////////////////////////////////////////////////////
		// ENCODING : process, load
		rEye.encode(mGaborFilters) ;

		/////////////////////////////////////////////////////////////////
		// SAVE
		// Save parameters
		rEye.saveParameters(mOutputDirParameters+short_name+mSuffixParameters) ;
		// Save mask
		rEye.saveMask(mOutputDirMasks+short_name+mSuffixMasks) ;
		// Save normalized image
		rEye.saveNormalizedImage(mOutputDirNormalizedImages+short_name+mSuffixNormalizedImages) ;
		// Save normalized mask
		rEye.saveNormalizedMask(mOutputDirNormalizedMasks+short_name+mSuffixNormalizedMasks) ;
		// Save iris code
		rEye.saveIrisCode(mOutputDirIrisCodes+short_name+mSuffixIrisCodes) ;  

		return 0;
	} // end of function

	int OsiManager::loadEye ( const string & rFileName , OsiEye & rEye )
	{
		OsiStringUtils osu ;
		string short_name = osu.extractFileName(rFileName) ;

		// Load normalized mask
		rEye.loadNormalizedMask(mInputDirNormalizedMasks+short_name+mSuffixNormalizedMasks) ;

		// Load iris code
		rEye.loadIrisCode(mInputDirIrisCodes+short_name+mSuffixIrisCodes) ;

		return 0;
	} // end of function

	void OsiManager::process(string filename)
	{
		try
		{
			OsiEye eye ;
			processEye(filename, eye) ;  
		}
		catch ( exception & e )
		{
			cout << e.what() << endl ;                
		}
	}

	float OsiManager::match(string filename1, string filename2)
	{
		float val = 0;

		try
		{
			OsiEye eye1, eye2 ;
			loadEye(filename1, eye1) ;  
			loadEye(filename2, eye2) ; 
			val = eye1.match(eye2, mpApplicationPoints);
		}
		catch ( exception & e )
		{
			cout << e.what() << endl ;                
		}

		return val;
	}

} // end of namespace

OsiManager.h

#ifndef OSI_MANAGER_H
#define OSI_MANAGER_H

#include <iostream>
#include <vector>
#include "highgui.h"
#include "OsiEye.h"

namespace osiris
{
    class OsiManager
    {
    public :
        OsiManager ( ) ;
        ~OsiManager ( ) ;

	void process(std::string filename);
	float match(std::string filename1, std::string filename2);

    private :
        //private变量不修改

        // Private methods
        //////////////////
        void initConfiguration ( ) ;
        void loadGaborFilters ( ) ;
        void loadApplicationPoints ( ) ;

	int processEye ( const std::string & rFileName , OsiEye & rEye );
	int loadEye ( const std::string & rFileName , OsiEye & rEye );
    } ; // End of class
} // End of namespace
#endif

可见，主要是增加了两个接口函数process()和match()，分别用于虹膜计算和虹膜对比；

3.在对话框程序中新建一个button：

void CosirismfcDlg::OnBnClickedButton1()
{
	cvNamedWindow("img", 1);
	cvNamedWindow("segment", 1);

	IplImage* img1 = cvLoadImage( "./SourceImage/S5000R00.jpg", CV_LOAD_IMAGE_GRAYSCALE );
	cvShowImage( "img", img1 );
	theManager.process("S5000R00.jpg");
	IplImage* seg1 = cvLoadImage( "./SegmentedImages/S5000R00_segm.bmp", CV_LOAD_IMAGE_COLOR );
	cvShowImage( "segment", seg1 );

	cvNamedWindow("img2", 1);
	cvNamedWindow("segment2", 1);
	IplImage* img2 = cvLoadImage( "./SourceImage/S5000R01.jpg", CV_LOAD_IMAGE_GRAYSCALE );
	cvShowImage( "img2", img2 );
	theManager.process("S5000R01.jpg");
	IplImage* seg2 = cvLoadImage( "./SegmentedImages/S5000R01_segm.bmp", CV_LOAD_IMAGE_COLOR );
	cvShowImage( "segment2", seg2 );

	if (theManager.match("S5000R00.jpg","S5000R01.jpg") < 0.32)
		MessageBox("S5000R00 and S5000R01 is same person");

	cvNamedWindow("img3", 1);
	cvNamedWindow("segment3", 1);
	IplImage* img3 = cvLoadImage( "./SourceImage/S5001R01.jpg", CV_LOAD_IMAGE_GRAYSCALE );
	cvShowImage( "img3", img3 );
	theManager.process("S5001R01.jpg");
	IplImage* seg3 = cvLoadImage( "./SegmentedImages/S5001R01_segm.bmp", CV_LOAD_IMAGE_COLOR );
	cvShowImage( "segment3", seg3 );

	if (theManager.match("S5000R00.jpg","S5001R01.jpg") > 0.32)
		MessageBox("S5000R00 and S5001R01 is not same person");
}

该button读取两张来自同一个人的虹膜图像，对比结果应当小于0.32；读取两张不同人的虹膜图像，对比结果应当大于0.32。

虹膜识别都要先进行process步骤，再进行match步骤。

4.把工程属性修改为不使用预编译头，编译；

5.在Release或Debug目录下新建如下几个文件夹：

CircleParameters
IrisCodes
Masks
NormalizedImages
NormalizedMasks
SegmentedImages
SourceImage

向SourceImage目录中拷贝如下示例虹膜图像：

S5000R00.bmp
S5000R01.bmp
S5000R02.bmp
S5001R00.bmp
S5001R01.bmp
S5001R02.bmp

并从OSIRIS源码中拷贝如下两个文件:

filters.txt
points.txt

然后就可运行exe文件了，运行结果：

本文完整工程可在qq群里下载：
虹膜识别算法研究QQ群：422376177
扫码加入：