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. Currently, in FIJI if you go to image>adjust>threshold you can move the sliders such that a certain percentage of the image is thresholded and it will display that value for you in the open window. Local thresholding techniques adapt the threshold value on each pixel to the local image characteristics. ImageJ provides several built-in methods for automatically computing a global threshold. 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. Thresholding is a technique for dividing an image into two (or more) classes of pixels, which are typically called “foreground” and “background.” Global thresholding Mean Gray Value - Average gray value within the selection. Area - Area of selection in square pixels.Area is in calibrated units, such as square millimeters, if Analyze>Set Scale was used to spatially calibrate the image.
#IMAGEJ THRESHOLD SELECTION HOW TO#
If you’d like to help, check out the how to help guide! Use this dialog box to specify which measurements are recorded by Analyze/Measure and Analyze/Analyze Particles. The content of this page has not been vetted since shifting away from MediaWiki.