直接对三通道的HObject 阈值分割 结果如何？

对哪些通道进行阈值分隔

猜测一：只对第一个通道进行阈值分割，可能有多个区域。
猜测二，对三个通道分别进行阈值分割，有多个区域。
个人感觉猜测一比较合理。假定猜测二正确，对结果用ReduceDomain ，各通道的结果会受其它通道干扰。

开发及运行环境。操作系统win7 开发工具：VS2022 图像处理库：halcon12CreateImage函数用于 指定宽度和byte数组创建图像
     

HObject CreateImage(byte[] barr,int width)
        {
            IntPtr p = Marshal.AllocHGlobal(barr.Length);
            Marshal.Copy(barr, 0, p, barr.Length);

            HObject img = new HObject();
            HOperatorSet.GenImage1(out img, "byte", width, barr.Length/ width,p);
//有内存泄漏
            return img;
        }

            int wh = 2;
            byte[] barr = new byte[wh * wh];
            HObject imgR = CreateImage(barr, wh);
            barr[0] = 1;
            HObject imgG = CreateImage(barr, wh);
            barr[1] = 1;
            HObject imgB = CreateImage(barr, wh);
            HObject imgRGB;
            HOperatorSet.Compose3(imgR, imgG, imgB, out imgRGB);
            HObject region;
            HOperatorSet.Threshold(imgRGB, out region, 1, 1);
            HTuple tNum;
            HOperatorSet.CountObj(region, out tNum);
            HTuple tArea = WHCSHalCon.Base.Area(region);

            结果：
区域数量1，面积0。
 修改组成多通道的语句为如下：
HOperatorSet.Compose3(imgG, imgB, imgR, out imgRGB);
区域数量1，面积1。
 修改组成多通道的语句为如下：
HOperatorSet.Compose3( imgB, imgR, imgG, out imgRGB);
区域数量1，面积2。

结论证明猜测一正确。

用时

新问题，直接二值化imgRGB用时会不会大幅增加呢？
 

int wh = 1024*10;
            byte[] barr = new byte[wh * wh];
            HObject imgR = CreateImage(barr, wh);
            barr[0] = 1;
            HObject imgG = CreateImage(barr, wh);
            barr[1] = 1;
            HObject imgB = CreateImage(barr, wh);
            HObject imgRGB;
            HOperatorSet.Compose3( imgB, imgR, imgG, out imgRGB);

            double dUse1, dUse2, dUse3;
            {
                System.DateTime begin = System.DateTime.Now;
                HObject region;
                HOperatorSet.Threshold(imgRGB, out region, 1, 1);
                HTuple tNum;
                HOperatorSet.CountObj(region, out tNum);
                HTuple tArea = WHCSHalCon.Base.Area(region);
                dUse1 = (System.DateTime.Now - begin).TotalMilliseconds;
            }

            {
                System.DateTime begin = System.DateTime.Now;
                HObject region;
                HOperatorSet.Threshold(imgR, out region, 1, 1);
                HTuple tNum;
                HOperatorSet.CountObj(region, out tNum);
                HTuple tArea = WHCSHalCon.Base.Area(region);
                dUse2 = (System.DateTime.Now - begin).TotalMilliseconds;
            }

            {
                System.DateTime begin = System.DateTime.Now;
                HObject tmp1, tmp2, tmp3;
                HOperatorSet.Decompose3(imgRGB, out tmp1, out tmp2, out tmp3);
                HObject region;
                HOperatorSet.Threshold(tmp1, out region, 1, 1);
                HTuple tNum;
                HOperatorSet.CountObj(region, out tNum);
                HTuple tArea = WHCSHalCon.Base.Area(region);
                dUse3 = (System.DateTime.Now - begin).TotalMilliseconds;
            }
        }

对于100M的大img，dUse1到15毫秒，dUse2大约7.8毫秒，dUse3大约8.2毫秒。增加的用时不能忽略