基于Hash的结合纹理和颜色的图像相似度算法 #OpenCV #C++

isHashSimilar.cpp

bool isHashSimilar(cv::UMat imageUMat, cv::UMat templUMat, cv::Point matchLoc, int threshold) {
    /*根据获取到的坐标从源图像截取子图并判断图像是否相似*/
    //截取子图
    cv::UMat imgUMat = imageUMat(cv::Range(matchLoc.y, matchLoc.y + templUMat.rows),
                                 cv::Range(matchLoc.x, matchLoc.x + templUMat.cols));

    //声明存放Hash结果数据的矩阵
    cv::UMat imgPHashMat = cv::UMat(1, 8, CV_8U);
    cv::UMat templPHashMat = cv::UMat(1, 8, CV_8U);
    cv::UMat imgColorMomentHashMat = cv::UMat(1, 42, CV_64F);
    cv::UMat templColorMomentHashMat = cv::UMat(1, 42, CV_64F);

    //PHash
    //获取pHash类的智能指针并调用类的create()方法初始化
    cv::Ptr<cv::img_hash::PHash> pHashPtr(cv::img_hash::PHash::create());
    //计算pHash结果数组
    pHashPtr->compute(imgUMat, imgPHashMat);
    pHashPtr->compute(templUMat, templPHashMat);
    //计算汉明距离
    double pHashCompareResult = pHashPtr->compare(imgPHashMat, templPHashMat);

    //ColorMomentHash
    cv::Ptr<cv::img_hash::ColorMomentHash> colorMomentHashPtr(
            cv::img_hash::ColorMomentHash::create());
    colorMomentHashPtr->compute(imgUMat, imgColorMomentHashMat);
    colorMomentHashPtr->compute(templUMat, templColorMomentHashMat);
    //计算欧几里得距离
    double colorMomentHashCompareResult = colorMomentHashPtr->compare(imgColorMomentHashMat,
                                                                      templColorMomentHashMat);

    if (pHashCompareResult <= threshold && colorMomentHashCompareResult <= threshold) {
        return 1;
    } else {
        return 0;
    }
}