#include <cv.h>

include <highgui.h>
include <stdlib.h>
//計算圖像感知hash值。詳情看：http://blog.csdn.net/lhfslhfs/article/details/9157845
int64 CalcImagePerceptualHashKey(const IplImage pImage)
{
    IplImage pTheImage8X8 = cvCreateImage(cvSize(8, 8), pImage->depth, pImage->nChannels);
    IplImage* pGrayscaleImage = cvCreateImage(cvSize(8, 8), 8, 1);

cvResize(pImage, pTheImage8X8, CV_INTER_AREA);
cvConvertImage(pTheImage8X8, pGrayscaleImage);
cvReleaseImage(&pTheImage8X8);

//計算平均值
float fElementMean = 0;
for (int y = 0; y < 8; ++y)
{
    for (int x = 0; x < 8; ++x)
    {
        unsigned char& cElem = *(unsigned char*)(pGrayscaleImage->imageData + x + y * pGrayscaleImage->widthStep);
        cElem = (unsigned char)(cElem / (float)255 * 64);
        fElementMean += cElem;
    }
}

fElementMean /= 64;
unsigned char cElementKey = 0;
int64 key = 0;
unsigned char* pKeyPtr = (unsigned char*)&key;

for (int y = 0; y < 8; ++y)
{
    for (int x = 0; x < 8; ++x)
    {
        if (fElementMean > *(unsigned char*)(pGrayscaleImage->imageData + x + y * pGrayscaleImage->widthStep))
        {
            //小于平均值即為0。
            cElementKey <<= 1;
        }
        else
        {
            //否則即為1
            cElementKey <<= 1;
            cElementKey |= 1;
        }
    }

    pKeyPtr[y] = cElementKey;
}

cvReleaseImage(&pGrayscaleImage);
return key;

}
//比較2個key的相似度，結果以1為最相似，0為不相似。
float CompareImageKeySimilarity(int64 key1, int64 key2)
{
    int64 keyResult = key1 ^ key2;
    int nOneCount = 0;
    int i = 64;
    while(i--)
    {
        if ((keyResult & 1) == 1)
            nOneCount++;

    keyResult >>= 1;
}

printf("nOneCount = %dn", nOneCount);
return nOneCount == 0 ? 1 : (64 - nOneCount) / (float)64;

}
int main(int argc, char argv[])
{
    IplImage pSrc1 = cvLoadImage("D:\cvImg\gujinlin1.jpg");
    IplImage* pSrc2 = cvLoadImage("D:\cvImg\gujinlin2.jpg");
    int64 key1 = CalcImagePerceptualHashKey(pSrc1);
    int64 key2 = CalcImagePerceptualHashKey(pSrc2);

printf("key1 = 0x%llX, key2 = 0x%llX, Similarity = %.2fn", key1, key2, CompareImageKeySimilarity(key1, key2));
return 0;

}</pre>