So, describing which method you use-and/or showing a comparison with other methods-is probably the best you can do to enable a statement on the quality of the extraction.įor more detailed information on thresholding and image segmentation basics and some quality evaluation see the Principles page. But such a ground truth is not naturally existing and is always created in one or the other way by a human. The basic problem of deciding if a threshold (or in general an extraction method) is “good” needs a “ground truth”. It will always be, to some extent, in the eye of the user/observer/scientist and will also be impacted by empirically collected knowledge. FAQ How do I know whether my threshold is correct? The ImageJ Ops project provides algorithms for both global and local thresholding. Local thresholding techniques adapt the threshold value on each pixel to the local image characteristics. Documentation for the threshold command.ImageJ provides several built-in methods for automatically computing a global threshold. Its central goal is to broaden the paradigm of ImageJ beyond the limitations of the original ImageJ application, to support the next generation of multidimensional scientific imaging. Global thresholding works by choosing a value cutoff, such that every pixel less than that value is considered one class, while every pixel greater than that value is considered the other class. ImageJ2 is a rewrite of ImageJ for multidimensional image data, with a focus on scientific imaging. Thresholding is a technique for dividing an image into two (or more) classes of pixels, which are typically called “foreground” and “background.” Global thresholding If you’d like to help, check out the how to help guide! ![]() The content of this page has not been vetted since shifting away from MediaWiki.
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