分水岭算法检测到的物体区域

时间:2019-01-11 22:37:22

标签: python opencv image-processing image-segmentation watershed

我正在使用分水岭算法来检测树冠。图像由无人机拍摄,其显示如下。 我想分别获取每棵树的面积(像素数),但我不知道该怎么做。

代码

img = cv2.imread("subset3.tif")
imgray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
thresh = cv2.adaptiveThreshold(imgray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 713, 9)

# noise removal
kernel = np.ones((9,9),np.uint8)
opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 3)

# sure background area
sure_bg = cv2.dilate(opening,kernel,iterations=3)

# Finding sure foreground area
dist_transform = cv2.distanceTransform(opening,cv2.DIST_L2,3)
ret, sure_fg = cv2.threshold(dist_transform,0.005*dist_transform.max(),255,0)

# Finding unknown region
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg,sure_fg)

# Marker labelling
ret, markers = cv2.connectedComponents(sure_fg)

# Add one to all labels so that sure background is not 0, but 1
markers = markers+1

# Now, mark the region of unknown with zero
markers[unknown==255] = 0

#Apply watershed()
markers = cv2.watershed(img,markers)
img[markers == -1] = [0,255,0]

Image

1 个答案:

答案 0 :(得分:0)

基本上 android:allowTaskReparenting="true" android:launchMode="singleTask" 是分量的数量,ret标记每个像素所属的分量。所以我们可以算一下:

makers

您可能需要更改为area =[np.sum(markers==val) for val in range(ret)] ,因为我们已经转移了range(1, ret+1)