使用阈值分割图像的一部分
我试图隔离并分割黄色车身以改变它的颜色。为了做到这一点，我需要将身体与图像分开识别。并继续用剩余的白色像素进行演讲。我使用 C#，这里的计划
Color d;
Color newColor = Color.YellowGreen;
for(inti =0;i<carimage.Width;i++){
for(intj =0;j<carimage.Height;j++){
d = carimage.GetPixel(i, j);
if(d.R == 255 && d.G==255 && d.B == 255)
image.SetPixel(i, j, newColor );
}
}
简单阈值处理将丢弃车身未正确分离的第二张图像。我尝试了 Aforge.net 填充孔图像过滤器，但阈值图像没有发生重大变化。我尝试使用滤色器，但由于主体的颜色变化，我没有返回正确的输出。任何人都可以为此提出建议和解决方案吗？
原始图像
阈值图像
Im trying to isolate and segment the yellow car body to change the color of it. in order to do that i need to separately identify the body from the image. And continue oration with the remaining white pixels. And im using C#, here the plan
Color d;
Color newColor = Color.YellowGreen;
for(inti =0;i<carimage.Width;i++){
for(intj =0;j<carimage.Height;j++){
d = carimage.GetPixel(i, j);
if(d.R == 255 && d.G==255 && d.B == 255)
image.SetPixel(i, j, newColor );
}
}
simple thresholding will trow the second image where car body is not separated correctly. i tried Aforge.net Fill holes image filter but no significant change has been done to the threshold image. I tried to use color filter but it i did not return a correct output due to color vary of the body. can anyone suggest and solution for this?
Original Image
Threshold Image
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评论（4）
您可能想要研究聚类，而不是阈值化。
作为快速和肮脏的测试，我增加了 HSB 空间中的图像亮度（使用 Mathematica）：
然后我使用了简单的 K-Nearest 聚类：
进行着色以查找图像中相似颜色的簇（还有更多） ，可能更合适的聚类算法，所以你应该尝试一下）。然后我可以调整其中一个簇的颜色：
如果您想使用阈值处理，您可能应该使用 CIE 色彩空间，因为该色彩空间中的欧几里得距离更接近人类的感知。
Instead of thresholding, you might want to look into clustering.
As a quick&dirty test, I've increased the image brightness in HSB space (using Mathematica):
Then I've used simple K-Nearest clustering:
to find clusters of similar colors in the image (there are many more, probably more suitable clustering algorithms, so you should experiment a little). Then I can just adjust the color in one of the clusters:
If you want to use thresholding, you should probably use a CIE color space, since euclidian distances in that color space are closer to human perception.
几年前我有一个类似的项目。我不记得确切的细节，但想法是在图像上移动一个（不太小的）滑动窗口，并计算窗口内每个位置的平均强度（可能分别针对 R、G 和 B）。我用这些平均值填充了“阈值图像”，并从原始图像中减去它。某处存在缩放因子以及其他调整内容，但重点是，这种方法比使用恒定阈值要好得多。
I had a similar project few years ago. I can't remember the exact details, but the idea was to shift a (not too small) sliding window over the image, and calculate the average intensity (maybe for R, G and B separately) inside the window at each position. I filled a "threshold image" with these averages, and subtracted it from the original image. There was a scaling factor somewhere, and other tuning stuff, but the point is, such an approach was way better than using a constant threshold.
如果您要使用一组阈值，则最好在色相饱和度值中选择黄色色调 色彩空间。请参阅相关的SO问题。
If you are going to use a set of thresholds, you might be better of selecting yellow hues in the Hue Saturation Value colorspace. See the related SO question.
给我：
通过查看图像的直方图，我得到了 0.64 阈值。我建议你使用MATLAB进行图像处理，因为它更容易。希望对您为图像着色有所帮助。
Gives me :
I got the 0.64 threshold by looking at the image's histogram. I suggest you use MATLAB to do image processing as it is much easier. Hope that helps you in colouring the image.