{"id":1112,"date":"2014-07-31T13:54:00","date_gmt":"2014-07-31T17:54:00","guid":{"rendered":"https:\/\/blogs.mathworks.com\/steve\/?p=1112"},"modified":"2019-11-01T11:15:38","modified_gmt":"2019-11-01T15:15:38","slug":"filling-circles","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/steve\/2014\/07\/31\/filling-circles\/","title":{"rendered":"Filling circles"},"content":{"rendered":"

Today's blog post comes from the stream of image processing questions<\/a> over at MATLAB Answers<\/a>.<\/p>

User arjun<\/a> wanted to know how to remove circles from an image by specifying their center and radius<\/a>.<\/p>

Famous MATLAB Answer man Image Analyst<\/a> quickly gave a helpful reply.<\/p>

I thought it might be worth a little discussion here (plus, I wanted to point out the value of MATLAB Answers.)<\/p>

Typically, the process of answering the question started out with trying to understand the question better. \"What does remove<\/i> mean to you?\" asked Image Analyst. The answer came back, \"I want to make the pixels in the circle be black.\"<\/p>

OK, let's give that a try.<\/p>

I = imread('coins.png'<\/span>);\r\nimshow(I)\r\n<\/pre>\"\" 
(Hmm. Guess I didn't have any quarters in my pocket when I took this picture.)<\/p>
Suppose we want to set to black all the pixels centered at (X = 175, Y = 120) and with radius 35.<\/p>
I like Image Analyst's recommended procedure:<\/p>
  1. Compute a mask image<\/i>. Generally, the term mask<\/i> or mask image<\/i> means a binary image whose foreground pixels correspond to a set of pixels of interest.<\/li>
  2. Use logical indexing with the mask image to modify the desired pixels.<\/li><\/ol><\/div>
    Start with creating a mask image.<\/p>
    xc = 175;\r\nyc = 120;\r\nr = 33;\r\n\r\nx = 1:size(I,2);\r\ny = 1:size(I,1);\r\n[xx,yy] = meshgrid(x,y);\r\n\r\nmask = hypot(xx - xc, yy - yc) <= r;\r\n\r\nimshow(mask)\r\ntitle('Mask image'<\/span>)\r\n<\/pre>\"\" 
    Next, use logical indexing to modify the pixels of I<\/tt> corresponding to the foreground pixels of mask<\/tt>.<\/p>
    I2 = I;\r\nI2(mask) = 0;\r\nimshow(I2)\r\ntitle('Image with some pixels set to black'<\/span>)\r\n<\/pre>\"\" 
    And we just lost 5 cents.<\/p>
    Image Analyst pointed out that you can use this technique to set pixel values in the circle to any value you want. How about white:<\/p>
    I2(mask) = 255;\r\nimshow(I2)\r\ntitle('Image with some pixels set to white'<\/span>)\r\n<\/pre>\"\" 
    For fun, how about setting the pixels to the background color. How do we determine that? I might start by thresholding the original image.<\/p>
    bw = im2bw(I,graythresh(I));\r\nimshow(bw)\r\ntitle('Thresholded image'<\/span>)\r\n<\/pre>\"\" 
    Now fill in the holes.<\/p>
    bw = imfill(bw,'holes'<\/span>);\r\nimshow(bw)\r\ntitle('Thresholded image with holes filled'<\/span>)\r\n<\/pre>\"\" 
    Compute the mean value of the background pixels (using logical indexing again!).<\/p>
    bg_mean = mean(I(~bw))\r\n<\/pre>
    \r\nbg_mean =\r\n\r\n   66.9959\r\n\r\n<\/pre>
    Replace the pixels in the circle with the computed average background value.<\/p>
    I2(mask) = bg_mean;\r\nimshow(I2)\r\ntitle('Circle pixels filled with average background'<\/span>)\r\n<\/pre>\"\" 
    Let me point out two related Image Processing Toolbox functions. The roifill<\/tt><\/a> function can fill a region based on a mask; it fills pixels \"smoothly\" from the adjacent background pixels.<\/p>
    I3 = roifill(I,mask);\r\nimshow(I3)\r\ntitle('Circle pixels replaced using roifill'<\/span>)\r\n<\/pre>\"\" 
    I also want to mention imellipse<\/tt><\/a>. You can use this function to draw circles interactively using the mouse. Then you can use the createMask<\/tt> function to get the mask image corresponding to the circle you drew.<\/p>
    Happy circle filling!<\/p>