等温线轮廓绘制灰度图像

Question

我有灰色的scae图像，想用等温线转换为强度轮廓，在我的代码中我只得到一个轮廓，以及如何应用等温线？

Answer 1

这是Python / OpenCV中的另一种方法，通过量化灰度图像然后获取轮廓。

• 阅读输入内容
• 将其转换为灰色
• 量化它
• 获取Canny优势
• 紧密应用形态学以确保其闭合
• 获取轮廓
• 按周长过滤轮廓，以去除多余的小轮廓
• 在输入上绘制轮廓
• 保存结果

输入：

import numpy as np
import cv2

# read input
img = cv2.imread('bright_blob.png')

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# do color quantization
gray = 64*((gray/64).astype(np.uint8))

# get canny edges
edges = cv2.Canny(gray, 10, 250)

# apply morphology closed to ensure they are closed
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
edges = cv2.morphologyEx(edges, cv2.MORPH_CLOSE, kernel)

# get contours
contours = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
contours = contours[0] if len(contours) == 2 else contours[1]

# filter contours to keep only large ones
result = img.copy()
for c in contours:
    perimeter = cv2.arcLength(c, True)
    if perimeter > 200: 
        cv2.drawContours(result, c, -1, (0,0,255), 1)

# save results
cv2.imwrite("bright_blob_gray.jpg", gray)
cv2.imwrite("bright_blob_edges.jpg", edges)
cv2.imwrite("bright_blob_isotherms.jpg", result)

# show images
cv2.imshow("gray", gray)
cv2.imshow("edges", edges)
cv2.imshow("result", result)
cv2.waitKey(0)

量化的灰度图像：

边缘图像：

结果：

Answer 2

您处在正确的轨道上，您所要做的只是将您硬编码到代码中的127进行迭代，并遍历几个不同的值。因此，请利用您所拥有的，然后添加一些内容（包括viridis colormap的插件）：

import numpy as np
import cv2 

# I don't have your image, so I will just create a similar one.
H, W = 480, 640 
img = np.zeros([H, W, 3], dtype=np.uint8)
cv2.circle(img, (W//2, H//2), 200, (255,255,255), -1) 
img = cv2.GaussianBlur(img, (551, 551), 0)
imgray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# The viridis colormap is better than the jet one you have used.
img_viridis = cv2.applyColorMap(imgray, cv2.COLORMAP_VIRIDIS)

# This for-loop allows you to draw isotherm lines at any value you want.
THRESHES = [30, 90, 170]
for val in THRESHES:
    ret, thresh = cv2.threshold(imgray, val, 255, 0)
    contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, 
                          cv2.CHAIN_APPROX_SIMPLE)
    cv2.drawContours(img_viridis, contours, -1, (0, 0, 255), 2)

cv2.imshow('img', img_viridis)
k = cv2.waitKey(0)

输出：