For this purpose I use the binary Close- operation, but the default settings do not work for me. I observe that the results change significantly in the result of small changes in Iterations and Count parameters. I read the description Process Menu , but feel that do not understand the meaning of the Count parameter.

The page text says:. Count specifies the number of adjacent background pixels necessary before a pixel is removed from the edge of an object during erosion and the number of adjacent foreground pixels necessary before a pixel is added to the edge of an object during dilation.

I just realised that the image above is not in the bit depth that the binary operations ImageJ would expect. Unless you are using a different program, the image should be 0 and the uploaded one has values of 0 and 1 and a non-accessible LUT. You can multiply by the image and apply the gray. lut to make it processable and visible in IJ.

erode 5 times. For instance if you set it to 7 for a dilation with white as foreground and black as background only those background pixels with 7 or more foreground neighbours get dilated. For the traditional binary morphological operations erode, dilate, open, close, etc. both settings should be set to 1. Say, we a 3x3 vicinity of a pixel, where the target pixel occupies the central position. Now how does Count actually work? I attach the original image shown above. I find it easy to think that the procedure counts the number of pixels around each background pixel that in the case of the white foreground are white.

It is checked or counted to decide whether to apply the morphological operation or not. Load you example and run this:. The above will only fill single background pixels i. surrounded by 8 neighbours. Change the count in line 5 to a different value to see the result which appears in grey in the result image.

Exclude Edge Maxima applies to the maximum, not to the particle. Find Maxima applied to a noisy image with different options Exclude Edge Maxima selected. Find Maxima does not work on stacks, but the FindStackMaxima macro runs it on all the images in a stack and creates a second stack containing the output images.

Replaces each pixel with the minimum lightest value in the 3×3 neighborhood. With binary images, removes pixels from the edges of black objects. Replaces each pixel with the maximum darkest value in the 3×3 neighborhood.

With binary images, adds pixels to the edges of black objects. Performs an erosion operation, followed by dilation. With binary images, this smooths objects and removes isolated pixels.

Performs a dilation operation, followed by erosion. With binary images, this smooths objects and fills in small holes. Display a dialog box that allows several settings used by commands in the Binary submenu to be altered. Iterations specifies the number of times erosion, dilation, opening, and closing are performed.

Count specifies the number of adjacent background pixels necessary before a pixel is removed from the edge of an object during erosion and the number of adjacent foreground pixels necessary before a pixel is added to the edge of an object during dilation.

Set it to overwrite for 8-bit output that overwrites the input image; 8-bit , bit or bit for separate output images. Generates a one pixel wide outline of foreground black objects in a binary image. The line is drawn inside the object, i.

Repeatably removes pixels from the edges of objects in a binary image until they are reduced to single pixel wide skeletons. Objects are assumed to be black and background white. Note that there exist many skeletonizing algorithms.

Generates a Euclidian distance map EDM. Each foreground pixel in the binary image is replaced with a gray value equal to that pixel's distance from the nearest background pixel. Generates the ultimate eroded points UEPs of the EDM. Requires a binary image as input. The UEPs represent the centers of particles that would be separated by segmentation.

The UEP's gray value is equal to the radius of the inscribed circle of the corresponding particle. Watershed segmentation of the Euclidian distance map EDM is a way of automatically separating or cutting apart particles that touch Watershed separation of a grayscale image is available via the Find Maxima The Watershed command requires a binary image containing black particles on a white background. It first calculates the Euclidian distance map and finds the ultimate eroded points UEPs.

It then dilates each of the UEPs the peaks or local maxima of the EDM as far as possible - either until the edge of the particle is reached, or the edge of the region of another growing UEP. Watershed segmentation works best for smooth convex objects that don't overlap too much. Here is an Animation that shows how watershed segmentation works. Splits the image by lines of points having equal distance to the borders of the two nearest particles. Thus, the Voronoi cell of each particle includes all points that are nearer to this particle than any other particle.

For the case of the particles being single points, this is a Voronoi tessellation also known as Dirichlet tessellation. In the output, the value inside the Voronoi cells is zero; the pixel values of the dividing lines between the cells are equal to the distance to the two nearest particles. This is similar to a medial axis transform of the background, but there are no lines in inner holes of particles. skip to content ImageJ Documentation Wiki.

User Tools Log In. Site Tools Search.

image × 1. tif I need to isolate the black object to the left marked in blue and then Fill Holes to remove it: image × 1. For this purpose I use the binary Close- operation, but the default settings do not work for me. I observe that the results change significantly in the result of small changes in Iterations and Count parameters. I read the description Process Menu , but feel that do not understand the meaning of the Count parameter. The page text says:.

Count specifies the number of adjacent background pixels necessary before a pixel is removed from the edge of an object during erosion and the number of adjacent foreground pixels necessary before a pixel is added to the edge of an object during dilation.

I just realised that the image above is not in the bit depth that the binary operations ImageJ would expect. Unless you are using a different program, the image should be 0 and the uploaded one has values of 0 and 1 and a non-accessible LUT.

You can multiply by the image and apply the gray. lut to make it processable and visible in IJ. erode 5 times. For instance if you set it to 7 for a dilation with white as foreground and black as background only those background pixels with 7 or more foreground neighbours get dilated.

For the traditional binary morphological operations erode, dilate, open, close, etc. both settings should be set to 1. Say, we a 3x3 vicinity of a pixel, where the target pixel occupies the central position. Now how does Count actually work? I attach the original image shown above. I find it easy to think that the procedure counts the number of pixels around each background pixel that in the case of the white foreground are white. It is checked or counted to decide whether to apply the morphological operation or not.

Load you example and run this:. The above will only fill single background pixels i. surrounded by 8 neighbours. Change the count in line 5 to a different value to see the result which appears in grey in the result image. So this can be used as a constraint to control whether to apply the operation or not for each pixel.

In general when you read about morphological operations, normally this constraint is not considered if used, it should be specified so others can reproduce the process.

Hope it clarifies it. If your end goal is to actually get this image below then this macro performs it on your forum image. Thank you for sharing the snippet. I tested the macro, but got the following error:. Your two uploaded images do not have the same dimensions: Clipboard. There is no need to use ROIs and all the rest.

Try the lines below to fill all the irregularities. If you need the filled part, just subtract the original from the result. Circle, square, star or something else? binary , close. Fiji based on ImageJ 1. I tested the macro, but got the following error: However I will continue testing and hopefully make it work and produce the expected result. run "Maximum Guys, thank you very much! You have share the very useful methods to solve the task. A circle. See

Page Tools Show pagesource Old revisions Backlinks Back to top. Hi all, I am just starting using imageJ and do some macros. Above Lower Threshold - This option appears for thresholded images only Finds maxima above the lower threshold only. Make binary; Fill holes. Requires a binary image as input. However I have some doubts about how to customize the ImageJ toolbar. image × 1.

Categories:

• Forex Bitcoin
• Binary Options
• Forex Brokers
• Binary Options online
• Forex