Namely, it starts applying the threshold approach, and if it fails to find a valid mask, it applies the edges approach.Ī4. This approach is a sequential application of Algorithms A1 and A2. The process stops after a valid mask is found or when a number of iterations is reached.Ī3. In case that the method does not work, the number of iterations that the find edges operation is applied is increased. The second strategy does not directly binarise the image but it firstly finds the edges of the image, and subsequently binarise the image using the IsoData method. This straightforward approach is useful when the spheroid image can be clearly distinguished from the background of the image.Ī2. In those cases where such a direct approach does not produce a valid mask, we sequentially binarise the image, dilate it, fill the holes, erode the image, and, finally, apply the watershed operation. The first strategy is based on just binarising the spheroid images by using the IsoData method. In addition, several variants of our algorithm are combined to deal with those cases where a proper spheroid mask is not generated.Ī1. Particular casesĭue to the different nature of spheroid images, we have particularised our generic algorithm using 5 strategies that is, using different values for the 5 parameters of our segmentation algorithm. Namely, the procedure can be split into two steps: contour generation and contour refinement.Īn example of the application of our generic algorithm is presented in the following image. This process, that is diagrammatically described in the following figure, is based on the sequential application of several image processing techniques, such as edge detection or thresholding, and morphological operations like dilation or erosion. Given an image containing a spheroid, our generic algorithm aims to produce a mask for the region that contains such a spheroid. Finally, the application is capable of searching ZIP archives as well.A graphical interface built on top of ImageJ to employ SpheroidJ can be downloaded from here. You do the cleanup in the future, but not waste time on searching for the files again. Yet another option is to find duplicate files and then save their paths to a text file. It comes really handy when you just want to get rid of the mess, but doubt the necessity to actually delete the files. Not only does Duplicates Finder allow you to remove such files, but it also gives you an opportunity to move them to an isolated folder and then restore retaining the original location. In practice, it allows you save disk space by removing multiple instances of the same song or delete sets of test shots that your camera made in the burst mode. Which is more, this software finds MP3 files with similar ID3 tags, similar images and files with similar names and size. This compact application was specifically designed to automate the process of searching, identifying and deleting duplicate and void files scatted across your hard drive or any other media. Advanced Duplicates Finder will do the trick.Īdvanced Duplicates Finder possesses a simple wizard-driven interface which guides you through the process. If this is exactly the problem you are facing or will face in the nearest future, relax, as you are not in much of a trouble. When you think that the time has come to clean up and eradicate the obvious file redundancy, you suddenly realize that it will take you days to manually compare and delete duplicate files. However, this can hardly be called a rational way of storing data, let alone the fact that it creates a mess in your computer. As we don't really need to save disk space these days, we often toss files around, create backups, make multiple copies of folders and then completely forget about them. Modern hard drives can easily hold up to tens and hundreds of thousands files.
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