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Global histogram threshold using Otsu's method


T = otsuthresh(counts)
[T,EM] = otsuthresh(counts)



T = otsuthresh(counts) computes a global threshold T from histogram counts, counts, using Otsu's method [1]. T is a normalized intensity value that lies in the range [0, 1] that can be used with imbinarize to convert an intensity image to a binary image. Otsu's method chooses a threshold that minimizes the intraclass variance of the thresholded black and white pixels.

[T,EM] = otsuthresh(counts) returns the effectiveness metric, EM, which indicates the effectiveness of the thresholding. EM is in the range [0, 1].


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Read image into the workspace.

I = imread('coins.png');

Calculate a 16-bin histogram for the image.

[counts,x] = imhist(I,16);

Compute a global threshold using the histogram counts.

T = otsuthresh(counts);

Create a binary image using the computed threshold and display the image.

BW = imbinarize(I,T);

Input Arguments

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Histogram counts, specified as a real, nonsparse numeric vector of nonnegative values.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Output Arguments

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Global threshold value, returned as a numeric scalar of class double in the range [0, 1].

Effectiveness metric, returned as a numeric scalar of class double in the range [0, 1]. The lower bound is attainable only by histogram counts with all data in a single non-zero bin. The upper bound is attainable only by histogram counts with two non-zero bins.


[1] Otsu, N., "A Threshold Selection Method from Gray-Level Histograms," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, No. 1, 1979, pp. 62-66.

Extended Capabilities

Introduced in R2016a

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