threshold_isodata(image, nbins=256, return_all=False)
Histogram-based threshold, known as Ridler-Calvard method or inter-means. Threshold values returned satisfy the following equality:
threshold = (image[image <= threshold].mean() +
image[image > threshold].mean()) / 2.0
That is, returned thresholds are intensities that separate the image into two groups of pixels, where the threshold intensity is midway between the mean intensities of these groups.
For integer images, the above equality holds to within one; for floating- point images, the equality holds to within the histogram bin-width.
Input image.
Number of bins used to calculate histogram. This value is ignored for integer arrays.
If False (default), return only the lowest threshold that satisfies the above equality. If True, return all valid thresholds.
Threshold value(s).
Return threshold value(s) based on ISODATA method.
>>> from skimage.data import coinsSee :
... image = coins()
... thresh = threshold_isodata(image)
... binary = image > thresh
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.filters.thresholding.threshold_isodata
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