下图如何获得黑白图像? [英] how can i get a black and white image for the following picture?

问题描述

我想将图片准确地转换为黑白图像，其中种子将用白色表示，背景用黑色表示.我想在python opencv代码中使用它.请帮帮我

I want to convert the picture into black and white image accurately where the seeds will be represented by white color and the background as black color. I would like to have it in python opencv code. Please help me out

使用下面的给定代码，对于上述图片，我得到了很好的结果.现在，我有另一幅画，其阈值似乎不起作用.我该如何解决这个问题.我得到的输出如下图

I got good result for the above picture using the given code below. Now I have another picture for which thresholding doesn't seem to work. How can I tackle this problem. The output i got is in the following picture

此外，种子中还有一些凹痕，程序将其作为种子的边界，效果不佳，如下图所示.我如何使该程序忽略凹痕.在这种情况下，遮盖种子是个不错的选择.

also, there are some dents in the seeds, which the program takes it as the boundary of the seed which is not a good results like in the picture below. How can i make the program ignore dents. Is masking the seeds a good option in this case.

推荐答案

我将图像从BGR颜色空间转换为HSV颜色空间.

I converted the image from BGR color space to HSV color space.

然后我提取了色调频道:

然后我对其执行了阈值:

Then I performed threshold on it:

注意:

每当您在某些区域遇到困难时，请尝试在不同的色彩空间中工作，HSV色彩空间最为突出.

Whenever you face difficulty in certain areas try working in a different color space, the HSV color space being most prominent.

更新:

这是代码:

import cv2
import numpy as np

filename = 'seed.jpg'
img = cv2.imread(filename)  #---Reading image file---

hsv_img = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)  #---Converting RGB image to HSV
hue, saturation, value, = cv2.split(hsv_img)   #---Splitting HSV image to 3 channels---

blur = cv2.GaussianBlur(hue,(3,3),0)   #---Blur to smooth the edges---

ret,th = cv2.threshold(blur, 38, 255, 0)   #---Binary threshold---
cv2.imshow('th.jpg',th)

现在，您可以执行轮廓操作以突出显示您感兴趣的区域.试试看！！:)

Now you can perform contour operations to highlight your regions of interest also. Try it out!! :)

其他更新:

我发现轮廓高于某个约束以得到此结果:

I found the contours higher than a certain constraint to get this:

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