流域边界紧密围绕一个区域

我想在OpenCV中创建两个Blob的平均值。为了实现这一目标，我打算以下列方式预处理的图像上使用分水岭算法：流域边界紧密围绕一个区域

cv::Mat common, diff, processed, result; 
cv::bitwise_and(blob1, blob2, common); //calc common area of the two blobs 
cv::absdiff(blob1, blob2, diff);  //calc area where they differ 

cv::distanceTransform(diff, processed, CV_DIST_L2, 3); //idea here is that the highest intensity 
                 //will be in the middle of the differing area 
cv::normalize(processed, processed, 0, 255, cv::NORM_MINMAX, CV_8U); //convert floats to bytes 

cv::Mat watershedMarkers, watershedOutline; 
common.convertTo(watershedMarkers, CV_32S, 1./255, 1); //change background to label 1, common area to label 2 
watershedMarkers.setTo(0, processed); //set 0 (unknown) for area where blobs differ 

cv::cvtColor(processed, processed, CV_GRAY2RGB); //watershed wants 3 channels 
cv::watershed(processed, watershedMarkers); 
cv::rectangle(watershedMarkers, cv::Rect(0, 0, watershedMarkers.cols, watershedMarkers.rows), 1); //remove the outline 

//draw the boundary in red (for debugging) 
watershedMarkers.convertTo(watershedOutline, CV_16S); 
cv::threshold(watershedOutline, watershedOutline, 0, 255, CV_THRESH_BINARY_INV); 
watershedOutline.convertTo(watershedOutline, CV_8U); 
processed.setTo(cv::Scalar(CV_RGB(255, 0, 0)), watershedOutline); 

//convert computed labels back to mask (blob), less relevant but shows my ultimate goal 
watershedMarkers.convertTo(watershedMarkers, CV_8U); 
cv::threshold(watershedMarkers, watershedMarkers, 1, 0, CV_THRESH_TOZERO_INV); 
cv::bitwise_not(watershedMarkers * 255, result);

我的结果问题是，计算出的边界是（几乎）总是毗邻常见的两种斑点的面积。下面是图片：

输入标记（黑= 0，灰色= 1，白色= 2）

流域输入图像（距离变换结果）用得到的轮廓在红色得出：

我期望边界沿着输入的最大强度区域（即沿着不同区域的中间）。相反（正如你所看到的），它主要围绕标记为2的区域，稍稍移动以触摸背景（标记为1）。我在这里做错了什么，或者我误解了分水岭是如何工作的？

来源

2017-02-09 slawekwin

见[此]（http://stackoverflow.com/questions/31961240/opencv-watershed-segmentation-miss-some-objects?rq=1） –

@JeruLuke感谢，但不是这样。我的背景具有标签1和对象2. – slawekwin

反转距离变换，使距离较远的点具有较小的值。在'normalize'行之后加上'processed = 255 - processed'。 – Miki

从这一形象开始：

你可以得到正确的结果只是传递一个全零图像分水岭算法。所述“盆”然后同样填充的“水”从每个开始“侧面”（然后只记得，以除去其由缺省通过分水岭算法设置为-1外边界）：

代码：

#include <opencv2\opencv.hpp> 

using namespace cv; 
using namespace std; 

int main() 
{ 
    Mat1b img = imread("path_to_image", IMREAD_GRAYSCALE); 

    Mat1i markers(img.rows, img.cols, int(0)); 
    markers.setTo(1, img == 128); 
    markers.setTo(2, img == 255); 

    Mat3b image(markers.rows, markers.cols, Vec3b(0,0,0)); 
    markers.convertTo(markers, CV_32S); 
    watershed(image, markers); 

    Mat3b result; 
    cvtColor(img, result, COLOR_GRAY2BGR); 
    result.setTo(Scalar(0, 0, 255), markers == -1); 

    imshow("Result", result); 
    waitKey(); 

    return(0); 
}

来源

2017-02-09 13:52:16 Miki

流域边界紧密围绕一个区域

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