Haclon和c#对比两张图片差异

haclon源码

read_image (Image, 'C:/Users/bayinglong/Desktop/搜狗截图20181206101404.png')
read_image (Image1, 'C:/Users/bayinglong/Desktop/搜狗截图20181206101426.png')
rgb1_to_gray (Image, GrayImage1)
rgb1_to_gray (Image1, GrayImage2)
abs_diff_image ( GrayImage1,  GrayImage2, ImageAbsDiff, 1)
a:=0
get_image_size (ImageAbsDiff, Width, Height)
gen_rectangle1 (Rectangle, 1,1,Height,Width)
intensity (Rectangle, ImageAbsDiff, Mean, Deviation)

主要流程，
1.两张图片相减少
2.相减图片求平均值和方差；

c#核心代码

public bool Extcute(out double Deviation, HImage bitmap1, HImage bitmap2)
        {
            try
            {
                ho_GrayImage1.Dispose();
                HOperatorSet.Rgb1ToGray(bitmap1, out ho_GrayImage1);
                ho_GrayImage2.Dispose();
                HOperatorSet.Rgb1ToGray(bitmap2, out ho_GrayImage2);
                ho_ImageAbsDiff.Dispose();
                HOperatorSet.AbsDiffImage(ho_GrayImage1, ho_GrayImage2, out ho_ImageAbsDiff, 1);
                HOperatorSet.GetImageSize(ho_ImageAbsDiff, out hv_Width, out hv_Height);
                ho_Rectangle.Dispose();
                HOperatorSet.GenRectangle1(out ho_Rectangle, 1, 1, hv_Height, hv_Width);
                HOperatorSet.Intensity(ho_Rectangle, ho_ImageAbsDiff, out hv_Mean, out hv_Deviation);

                Deviation = (double)hv_Deviation;
                return true;
            }
            catch (System.Exception ex)
            {
                Deviation = 1000;
                return false;
            }
          
        }

利用图像句柄生成haclon Himage类

 /// <summary>
        /// 生成Himage
        /// </summary>
        /// <param name="bmp">图片句柄</param>
        /// <param name="width">图片宽</param>
        /// <param name="hight">图片高</param>
        /// <returns></returns>
        public HImage HImageConvertFromBitmap32(IntPtr bmp,int width,int hight)
        {

            HalconDotNet.HImage img = new HalconDotNet.HImage();
            img.GenImage1("byte", width, hight, bmp);
            return img;
        }