[人工智能]使用OpenCV实现Halcon算法（6）dyn_threshold算子

先看halcon算子的使用：

read_image (Image,'photometric_stereo/embossed_01')
mean_image (Image,ImageMean,60,60)
dyn_threshold (Image, ImageMean, RegionDynThresh, 15, 'not_equal')

再看OpenCV的实现：

void CImagePreprocessing::dynamic_threshold_referHalcon(cv::Mat &frame_gray, int ksize, int offset) //仿Halcon
{
    cv::Mat srcMean;
    cv::Mat binary1;
    cv::Mat binary2;

    //均值滤波
    blur(frame_gray, srcMean, cv::Size(9, 9));

    //动态阈值
    binary1 = cv::Mat::zeros(frame_gray.size(), CV_8UC1);
    _HalconDynThreshold(frame_gray, srcMean, binary1, offset, Equal);
}

void CImagePreprocessing::_HalconDynThreshold(cv::Mat &src, cv::Mat &srcMean, cv::Mat &result, int offset, int LightDark)
{
    //使用Opencv实现Halcon中的动态阈值
    //src是原图,灰度图
    //srcMean是平滑滤波之后的图
    //最好不要把Offset这个变量设置为0，因为这样会导致最后找到太多很小的regions，而这基本上都是噪声。
    //所以这个值最好是在5-40之间，值选择的越大，提取出来的regions就会越小。
    int r = src.rows; //高
    int c = src.cols; //宽
    int Value = 0;
    for (int i = 0; i < r; i++)
    {
        uchar *datasrc = src.ptr<uchar>(i); //指针访问图像像素
        uchar *datasrcMean = srcMean.ptr<uchar>(i);
        uchar *dataresult = result.ptr<uchar>(i);

        for (int j = 0; j < c; j++)
        {
            switch (LightDark)
            {
            case Light:
                Value = datasrc[j] - datasrcMean[j];
                if (Value >= offset)
                {
                    dataresult[j] = 255;
                }
                break;

            case Dark:
                Value = datasrcMean[j] - datasrc[j];
                if (Value >= offset)
                {
                    dataresult[j] = 255;
                }
                break;

            case Equal:
                Value = datasrc[j] - datasrcMean[j];
                if (Value >= -offset && Value <= offset)
                {
                    dataresult[j] = 255;
                }
                break;

            case Not_equal:
                Value = datasrc[j] - datasrcMean[j];
                if (Value < -offset || Value > offset)
                {
                    dataresult[j] = 255;
                }
                break;

            default:
                break;
            }
        }
    }
}