{"id":111,"date":"2007-01-01T20:39:44","date_gmt":"2007-01-02T01:39:44","guid":{"rendered":"https:\/\/blogs.mathworks.com\/steve\/?p=111"},"modified":"2019-10-23T08:41:09","modified_gmt":"2019-10-23T12:41:09","slug":"superimposing-line-plots","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/steve\/2007\/01\/01\/superimposing-line-plots\/","title":{"rendered":"Superimposing line plots on images"},"content":{"rendered":"
\r\n\r\nSeveral people have asked me recently how to plot some kind of shape on top of an image, so I thought I'd show the basic technique\r\nhere. Essentially, you display the image, then call hold on<\/tt><\/a>, and then use plot<\/tt><\/a> or some other graphics command to superimpose the desired shape.\r\n\r\nFor my first example, I'll superimpose the boundaries found by the bwboundaries<\/tt><\/a> function on top of the original binary image.\r\n
bw = imread('circles.png'<\/span>);\r\nb = bwboundaries(bw);\r\nimshow(bw)<\/pre>\r\n\"\"\r\n\r\nNow call hold on<\/tt>. This causes subsequent plotting commands to add to what's already in the figure, instead of replacing it.\r\n
hold on<\/span><\/pre>\r\n\"\"\r\n\r\nFinally, call plot to superimpose the boundary locations.\r\n
for<\/span> k = 1:numel(b)\r\n    plot(b{k}(:,2), b{k}(:,1), 'r'<\/span>, 'Linewidth'<\/span>, 3)\r\nend<\/span><\/pre>\r\n\"\"\r\n\r\nIt's good to get in the habit of calling hold off<\/tt> when you're done adding plot elements. That way, the next high-level plotting command will start over, which is usually\r\nwhat is expected.\r\n\r\nMy second example shows how to superimpose a 25-pixel-by-25-pixel grid on an image. (See Natasha's blog comment<\/a>.) Display the image first, and then call hold on<\/tt>.\r\n
clf\r\nrgb = imread('peppers.png'<\/span>);\r\nimshow(rgb)\r\nhold on<\/span><\/pre>\r\n\"\"\r\n\r\nNow superimpose the grid. To make sure the grid is visible over all pixel colors, I'll use the trick of superimposing two\r\nline objects with contrasting colors and line styles. The Pixel Region Tool<\/a> in the Image Processing Toolbox uses this same trick.\r\n
M = size(rgb,1);\r\nN = size(rgb,2);\r\n\r\nfor<\/span> k = 1:25:M\r\n    x = [1 N];\r\n    y = [k k];\r\n    plot(x,y,'Color'<\/span>,'w'<\/span>,'LineStyle'<\/span>,'-'<\/span>);\r\n    plot(x,y,'Color'<\/span>,'k'<\/span>,'LineStyle'<\/span>,':'<\/span>);\r\nend<\/span>\r\n\r\nfor<\/span> k = 1:25:N\r\n    x = [k k];\r\n    y = [1 M];\r\n    plot(x,y,'Color'<\/span>,'w'<\/span>,'LineStyle'<\/span>,'-'<\/span>);\r\n    plot(x,y,'Color'<\/span>,'k'<\/span>,'LineStyle'<\/span>,':'<\/span>);\r\nend<\/span>\r\n\r\nhold off<\/span><\/pre>\r\n\"\"