OpenCV學(xué)習(xí)筆記3找出人臉-同時(shí)比較兩張圖片中的人臉相似度

OpenCV學(xué)習(xí)筆記3:找出人臉，同時(shí)比較兩張圖片中的人臉相似度

終于到了有實(shí)際應(yīng)用的功能了，有2張圖片，里面各有一個(gè)人臉，我的目的是比較這兩個(gè)人臉的相似度，這里用到了facedetect的功能，還有圖像轉(zhuǎn)換，圖像剪切，以及直方圖的比較。具體流程是:

1。分別用facedetect功能將兩張圖片中的人臉檢測(cè)出來

2。將人臉部分的圖片剪切出來，存到兩張只有人臉的圖片里。

3。將這兩張人臉圖片轉(zhuǎn)換成單通道的圖像

4。使用直方圖比較這兩張單通道的人臉圖像，得出相似度。

這里對(duì)圖的要求還是比較高的，光線和姿勢(shì)不能有差別，臉的垂直或者左右角度偏差就會(huì)影響比較，但和兩張圖片的大小關(guān)系不大，本人覺得較適合于證件照的對(duì)比。下面是代碼，其中haarcascade_frontalface_alt.xml是opencv里facedetect例子用的樣本。比較的是srcImage和targetImage對(duì)應(yīng)的文件.還有下面是IplImage和Mat混用，純當(dāng)熟悉這兩個(gè)類了。[cpp]

\o"viewplain"viewplain\o"copy"copy

[cpp]

\o"viewplain"viewplain\o"copy"copy

[cpp]

\o"viewplain"viewplain\o"copy"copy#include

"opencv/cv.hpp"

#include

"opencv2/objdetect/objdetect.hpp"

#include

"opencv2/highgui/highgui.hpp"

#include

"opencv2/imgproc/imgproc.hpp"

#include

<iostream>

#include

<stdio.h>

using

namespace

std;

using

namespace

cv;

String

cascadeName

=

"D:\\OpenCV-2.4.2\\data\\haarcascades\\haarcascade_frontalface_alt.xml";

IplImage*

cutImage(IplImage*

src,

CvRect

rect)

{

cvSetImageROI(src,

rect);

IplImage*

dst

=

cvCreateImage(cvSize(rect.width,

rect.height),

src->depth,

src->nChannels);

cvCopy(src,dst,0);

cvResetImageROI(src);

return

dst;

}

IplImage*

detect(

Mat&

img,

CascadeClassifier&

cascade,

double

scale)

{

int

i

=

0;

double

t

=

0;

vector<Rect>

faces;

Mat

gray,

smallImg(

cvRound

(img.rows/scale),

cvRound(img.cols/scale),

CV_8UC1

);

cvtColor(

img,

gray,

CV_BGR2GRAY

);

resize(

gray,

smallImg,

smallImg.size(),

0,

0,

INTER_LINEAR

);

equalizeHist(

smallImg,

smallImg

);

t

=

(double)cvGetTickCount();

cascade.detectMultiScale(

smallImg,

faces,

1.3,

2,

CV_HAAR_SCALE_IMAGE,

Size(30,

30)

);

t

=

(double)cvGetTickCount()

-

t;

printf(

"detection

time

=

%g

ms\n",

t/((double)cvGetTickFrequency()*1000.)

);

for(

vector<Rect>::const_iterator

r

=

faces.begin();

r

!=

faces.end();

r++,

i++

)

{

IplImage*

temp

=

cutImage(&(IplImage(img)),

cvRect(r->x,

r->y,

r->width,

r->height));

return

temp;

}

return

NULL;

}

//畫直方圖用

int

HistogramBins

=

256;

float

HistogramRange1[2]={0,255};

float

*HistogramRange[1]={&HistogramRange1[0]};

int

CompareHist(IplImage*

image1,

IplImage*

image2)

{

IplImage*

srcImage;

IplImage*

targetImage;

if

(image1->nChannels

!=

1)

{

srcImage

=

cvCreateImage(cvSize(image1->width,

image1->height),

image1->depth,

1);

cvCvtColor(image1,

srcImage,

CV_BGR2GRAY);

}

else

{

srcImage

=

image1;

}

if

(image2->nChannels

!=

1)

{

targetImage

=

cvCreateImage(cvSize(image2->width,

image2->height),

srcImage->depth,

1);

cvCvtColor(image2,

targetImage,

CV_BGR2GRAY);

}

else

{

targetImage

=

image2;

}

CvHistogram

*Histogram1

=

cvCreateHist(1,

&HistogramBins,

CV_HIST_ARRAY,HistogramRange);

CvHistogram

*Histogram2

=

cvCreateHist(1,

&HistogramBins,

CV_HIST_ARRAY,HistogramRange);

cvCalcHist(&srcImage,

Histogram1);

cvCalcHist(&targetImage,

Histogram2);

cvNormalizeHist(Histogram1,

1);

cvNormalizeHist(Histogram2,

1);

//

CV_COMP_CHISQR,CV_COMP_BHATTACHARYYA這兩種都可以用來做直方圖的比較，值越小，說明圖形越相似

printf("CV_COMP_CHISQR

:

%.4f\n",

cvCompareHist(Histogram1,

Histogram2,

CV_COMP_CHISQR));

printf("CV_COMP_BHATTACHARYYA

:

%.4f\n",

cvCompareHist(Histogram1,

Histogram2,

CV_COMP_BHATTACHARYYA));

//

CV_COMP_CORREL,

CV_COMP_INTERSECT這兩種直方圖的比較，值越大，說明圖形越相似

printf("CV_COMP_CORREL

:

%.4f\n",

cvCompareHist(Histogram1,

Histogram2,

CV_COMP_CORREL));

printf("CV_COMP_INTERSECT

:

%.4f\n",

cvCompareHist(Histogram1,

Histogram2,

CV_COMP_INTERSECT));

cvReleaseHist(&Histogram1);

cvReleaseHist(&Histogram2);

if

(image1->nChannels

!=

1)

{

cvReleaseImage(&srcImage);

}

if

(image2->nChannels

!=

1)

{

cvReleaseImage(&targetImage);

}

return

0;

}

String

srcImage

=

"d:\\ldh1.jpg";

String

targetImage

=

"d:\\ldh5.jpg";

int

main(int

argc,

char*

argv[])

{

CascadeClassifier

cascade;

namedWindow("image1");

namedWindow("image2");

if(

!cascade.load(

cascadeName

)

)

{

return

-1;

}

Mat

srcImg,

targetImg;

IplImage*

faceImage1;

IplImage*

faceImage2;

srcImg

=

imread(srcImage);

targetImg

=

imread(targetImage);

faceImage1

=

detect(srcImg,

cascade,

1);

if

(faceImage1

==

NULL)

{

return

-1;

}

//

cvSaveImage("d:\\face.jpg",

faceImage1,

0);

faceImage2

=

detect(targetImg,

cascade,

1);

if

(faceImage2

==

NULL)

{

return

-1;

}

//

cvSaveImage(