How do I isolate the layers of the given grayscale image?

Answer 1

[Takuji Fukumoto]

Here it is.

I = imread('point5.jpg');
Ig = rgb2gray(I);
imtool(Ig)
BW = Ig > 118;
BW2 = BW;
ext = logical(ones(numel(BW(:,1)),1));
BW2 = [ext BW2 ext];
% BW2(:,[1 end]) = 1;
BW2 = imdilate(BW2,ones(3));
BW2 = imfill(BW2,'holes');
BW2 = imerode(BW2,ones(3));
BWout = BW2(:,2:end-1);
figure ,imshow(BWout)

[The Imagician]

Thank you. But I am looking to separate the individual white and black layers within that image. Do you have any thoughts on approaches that would work?

[Takuji Fukumoto]

Like this?

I don't understand what you want to do. It would be nice if you draw the line in the picture.

[Image Analyst]

Explain in detail what the imprecise terms "isolate" and "separate" mean? Do you want a masked image? One image or two? Assuming you had them, what would you do with them?

I see as many as 12 layers in that grayscale image. Which are the layers you want and what distinguishes them from the neighboring layers. Please post an annotated layer where you indicate the layers in a red outline or something.

Please answer these questions only after you read this link.

[The Imagician]

Thank you Takuji Fukumoto. That is almost what I meant. Here is the annotated image. I need to extract each of these 3 layers of the image. Using the individual layers, I would like to fit a line and find the std. deviation to its upper and lower limits (as denoted in green) across various points along the length of the layer. To answer Image Analyst, no I don't need a masked image or multiple images. I just need to be able to calculate the aforementioned values for these 3 layers. Thank you.