[英]Get perimeter of pixels around centre pixel
I am attempting to get a circle of pixels around a centre pixel. 我试图在中心像素周围得到一个像素圈。 Ie, just like how FAST keypoint detector works, I want to get the perimeter pixels around it given a radius.
即,就像FAST关键点检测器的工作原理一样,我想在给定半径的情况下获取其周围的周边像素。 However the math escapes me, I know theoretically how I could obtain it using trigonometry.
无论数学如何,我从理论上都知道如何使用三角函数获得数学。 Ie, I could use a for loop and iterate at 15 degrees.
即,我可以使用for循环并以15度进行迭代。 I know the triangle hypotenuse length is the radius, I know the angle.
我知道三角形的斜边长度是半径,我知道角度。
Any advice how I could obtain a perimeter of pixels around a given pixel? 任何建议如何获得给定像素周围的像素周长?
The formula is: 公式为:
(x-cx)**2 + (y-cy)**2 = r**2
where cx and cy is the center of the circle and x and y are the coordinates you want to test... Now we can iterate over x and get the y with the formula like this: 其中cx和cy是圆的中心,x和y是要测试的坐标...现在,我们可以遍历x并使用如下公式获得y:
y = sqrt(r**2 - (x-cx)**2) + cy
The other way will be to iterate the 360 degrees and calculate the x and y and add the offset (center) like this: 另一种方法是迭代360度并计算x和y并添加偏移量(中心),如下所示:
x = cos(radians) * radius + cx
y = sin(radians) * radius + cy
The second version gave me a more complete circle in my tests. 第二版使我的测试更加完整。 Here is my test script in python:
这是我在python中的测试脚本:
import numpy as np
import cv2
import math
img = np.zeros((480, 640, 1), dtype="uint8")
img2 = np.zeros((480, 640, 1), dtype="uint8")
center = (200, 200)
radius = 100
x = np.arange(center[0] - radius, center[0]+radius+1)
y_off = np.sqrt(radius**2 - (x - center[0]) **2)
y1 = np.int32(np.round(center[1] + y_off))
y2 = np.int32(np.round(center[1] - y_off))
img[y1, x] = 255
img[y2, x] = 255
degrees = np.arange(360)
x = np.int32(np.round(np.cos(degrees) * radius)) + center[0]
y = np.int32(np.round(np.sin(degrees) * radius)) + center[1]
img2[y,x] = 255
cv2.imshow("First method", img)
cv2.imshow("Second method", img2)
cv2.waitKey(0)
cv2.destroyAllWindows()
and the results are these: 结果是:
Method 1 方法1
Method 2 方法二
There is a third method... You take a box around the circle of size radius x radius and evaluate each point with the circle formula given above, if it is true then it is a circle point... however that is good to draw the whole circle, since you have integers and highly probable not many point will be equal... 第三种方法...您在半径为半径x半径的圆周围取一个框,并使用上述给定的圆公式计算每个点,如果为true,则为圆点...但是绘制起来很不错整个圆圈,因为您有整数并且很可能没有多少点相等...
UPDATE: 更新:
Just a small reminder, make sure your points are in the image, in the example above, if you put the center in 0,0 it will draw 1/4 of a circle in every corner, because it considers the negative values to start from the end of the array. 提醒一下,请确保您的点在图像中,在上面的示例中,如果将中心置于0,0,则它将在每个角上绘制一个圆的1/4,因为它认为负值从数组的末尾。
To remove duplicates you can try the following code: 要删除重复项,您可以尝试以下代码:
c = np.unique(np.array(list(zip(y,x))), axis=0 )
img2[c[:,0], c[:,1]] = 255
Just draw the circle onto a mask: 只需将圆圈绘制到蒙版上:
In [27]: mask = np.zeros((9, 9), dtype=np.uint8)
In [28]: cv2.circle(mask, center=(4, 4), radius=4, color=255, thickness=1)
Out[28]:
array([[ 0, 0, 0, 0, 255, 0, 0, 0, 0],
[ 0, 0, 255, 255, 0, 255, 255, 0, 0],
[ 0, 255, 0, 0, 0, 0, 0, 255, 0],
[ 0, 255, 0, 0, 0, 0, 0, 255, 0],
[255, 0, 0, 0, 0, 0, 0, 0, 255],
[ 0, 255, 0, 0, 0, 0, 0, 255, 0],
[ 0, 255, 0, 0, 0, 0, 0, 255, 0],
[ 0, 0, 255, 255, 0, 255, 255, 0, 0],
[ 0, 0, 0, 0, 255, 0, 0, 0, 0]], dtype=uint8)
And now you can use it to index your image as you like. 现在,您可以根据需要使用它来索引图像。 Eg, here's a random image:
例如,这是一个随机图像:
In [33]: img
Out[33]:
array([[ 88, 239, 212, 160, 89, 85, 249, 242, 88],
[ 47, 230, 206, 206, 63, 143, 152, 67, 58],
[162, 212, 0, 213, 208, 169, 228, 14, 229],
[230, 45, 103, 201, 188, 231, 80, 122, 131],
[159, 31, 148, 158, 73, 215, 152, 158, 235],
[213, 177, 148, 237, 92, 115, 152, 188, 223],
[234, 67, 141, 173, 14, 18, 242, 208, 147],
[ 53, 194, 229, 141, 37, 215, 230, 167, 82],
[ 72, 78, 152, 76, 230, 128, 137, 25, 168]], dtype=uint8)
Here's the values on the perimeter: 这是周长上的值:
In [34]: img[np.nonzero(mask)]
Out[34]:
array([ 89, 206, 206, 143, 152, 212, 14, 45, 122, 159, 235, 177, 188,
67, 208, 229, 141, 215, 230, 230], dtype=uint8)
Setting the value of the image at the perimeter of the circle to 0: 将圆周围的图像值设置为0:
In [35]: img[np.nonzero(mask)] = 0
In [36]: img
Out[36]:
array([[ 88, 239, 212, 160, 0, 85, 249, 242, 88],
[ 47, 230, 0, 0, 63, 0, 0, 67, 58],
[162, 0, 0, 213, 208, 169, 228, 0, 229],
[230, 0, 103, 201, 188, 231, 80, 0, 131],
[ 0, 31, 148, 158, 73, 215, 152, 158, 0],
[213, 0, 148, 237, 92, 115, 152, 0, 223],
[234, 0, 141, 173, 14, 18, 242, 0, 147],
[ 53, 194, 0, 0, 37, 0, 0, 167, 82],
[ 72, 78, 152, 76, 0, 128, 137, 25, 168]], dtype=uint8)
You can easily get the coordinates as well: 您也可以轻松获取坐标:
In [56]: np.where(mask)
Out[56]:
(array([0, 1, 1, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 7, 7, 8]),
array([4, 2, 3, 5, 6, 1, 7, 1, 7, 0, 8, 1, 7, 1, 7, 2, 3, 5, 6, 4]))
Assume img
is your image, radius
is the radius of the circle and x, y
are the coordinates of the center around which you want to focus. 假设
img
是您的图像, radius
是圆的半径, x, y
是您要聚焦的中心的坐标。
The the focus_img
can be obtained using focus_img
可以使用
offset = math.ceil(radius * math.sqrt(2))
focus_img = img[y-offset:y+offset, x-offset:x+offset]
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.