OpenCV

Question

我正尝试在下面的图像上使用 floodFill 来提取天空：

但即使我设置了 loDiff=Scalar(0,0,0) 和 upDiff=Scalar(255,255,255)，结果也只是显示了种子点，并没有变大（绿点）：

代码：

Mat flood;
Point seed = Point(180, 80);
flood = imread("D:/Project/data/1.jpeg");
cv::floodFill(flood, seed, Scalar(0, 0, 255), NULL, Scalar(0, 0, 0), Scalar(255, 255, 255));
circle(flood, seed, 2, Scalar(0, 255, 0), CV_FILLED, CV_AA);

这是结果（红点是种子）：

如何设置函数以获得更大的区域（如整个天空）？

Answer 1

您需要正确设置 loDiff 和 upDiff 参数。

参见floodFill documentation：

loDiff – Maximal lower brightness/color difference between the currently observed pixel and one of its neighbors belonging to the component, or a seed pixel being added to the component.
upDiff – Maximal upper brightness/color difference between the currently observed pixel and one of its neighbors belonging to the component, or a seed pixel being added to the component.

这是一个 Python 代码示例：

import cv2
flood = cv2.imread("1.jpeg");

seed = (180, 80)

cv2.floodFill(flood, None, seedPoint=seed, newVal=(0, 0, 255), loDiff=(5, 5, 5, 5), upDiff=(5, 5, 5, 5))
cv2.circle(flood, seed, 2, (0, 255, 0), cv2.FILLED, cv2.LINE_AA);

cv2.imshow('flood', flood)
cv2.waitKey(0)
cv2.destroyAllWindows()

结果：

Answer 2

如果您希望填充轮廓尽可能接近图像中的对比元素，您可以做的另一件事是执行 Kmeans 颜色量化以将图像分割成指定数量的簇。由于天空和 mountains/trees 有明显的色差，我们可以将图像分割成三种颜色，这样可以更好地分离物体。

例如 clusters=3:

输入图像-> Kmeans颜色分割

Floodfill 结果为绿色

注意分割后如何只有三种颜色定义图像。这样，填充物将沿着mountains/trees更好

等高线

代码

import cv2
import numpy as np

# Kmeans color segmentation
def kmeans_color_quantization(image, clusters=8, rounds=1):
    h, w = image.shape[:2]
    samples = np.zeros([h*w,3], dtype=np.float32)
    count = 0

    for x in range(h):
        for y in range(w):
            samples[count] = image[x][y]
            count += 1

    compactness, labels, centers = cv2.kmeans(samples,
            clusters, 
            None,
            (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10000, 0.0001), 
            rounds, 
            cv2.KMEANS_RANDOM_CENTERS)

    centers = np.uint8(centers)
    res = centers[labels.flatten()]
    return res.reshape((image.shape))

# Load image and perform kmeans
image = cv2.imread('1.jpg')
kmeans = kmeans_color_quantization(image, clusters=3)
result = kmeans.copy()

# Floodfill
seed_point = (150, 50)
cv2.floodFill(result, None, seedPoint=seed_point, newVal=(36, 255, 12), loDiff=(0, 0, 0, 0), upDiff=(0, 0, 0, 0))

cv2.imshow('image', image)
cv2.imshow('kmeans', kmeans)
cv2.imshow('result', result)
cv2.waitKey()

OpenCV - 如何对 RGB 图像使用 floodFill？

OpenCV - How to use floodFill with RGB image?

c++

python

image-processing

flood-fill

代码：