使用线边缘进行Matlab图像分割

这些是边缘伪像。Canny在内部使用渐变，目前尚不清楚如何在图像边界处计算渐变（在matlab中也模糊了edge）。只需裁剪BW图像即可。

编辑：

The default value of sigma for gaussian blurring in edge is 1.41 pixels. So If you crop approximately twice that and additional 2 pixels to account for sobel kernel used to calculate gradient (5 pixels in total) from each edge (I mean edge of the image, not the detected edges), you'll get rid of the edge artifacts.

Like this

BW_cropped = BW(5:end-5,5:end-5)

Then add back those 5 pixels to each coordinate if your image processing involves finding positions of something in the image.

EDIT2:

For example to get all pixels in regions of cropped image use bwconncomp on inverted image like this:

CC=bwconncomp(not(BW_cropped),4);

Result:

>> CC

CC = 

    Connectivity: 4
       ImageSize: [471 631]
      NumObjects: 3
    PixelIdxList: {[40405x1 double]  [254682x1 double]  [1430x1 double]}

So you get and output structure , where field PixelIdxList gives you a three element (number of regions) of indeces of all pixels within your regions (indexing into the cropped_BW).

然后，您可以在regionprops功能中使用CC来获取有关您的区域的一些信息（例如区域或质心，请参阅所有选项的帮助）

编辑3：

示例代码：

a = imread('XEDCa.png');

I = rgb2gray(a);
BW = edge(I,'canny',0.6);
BW_cropped = BW(5:end-5,5:end-5);
CC=bwconncomp(not(BW_cropped),4)
imagesc(labelmatrix(CC))

结果：