# mmhistogram
Find the histogram of the image f.

## Synopsis

h = mmhistogram( f, option = "uint16" )

Implemented in Python.

### Input

f | Image Gray-scale (uint8 or uint16) or binary image.
option | String Values: "uint16" or "int32". Default: `"uint16"`

### Output

h | Image Gray-scale (uint8 or uint16) image. Histogram in a `uint16` or an `int32` vector.

## Description

Finds the histogram of the image `f` and returns the result in the vector `h`. For binary image the vector size is 2, for gray-scale uint8 and uint16 images, the vector size is the maximum pixel value plus one. `h[0]` gives the number of pixels with value 0.

## Examples

    >>> f=uint8([0, 1, 1, 2, 2, 2, 5, 3, 5])

    >>> h=mmhistogram(f)

    >>> print h

    [1 2 3 1 0 2]

    >>> f=mmreadgray('lenina.tif')

    >>> mmshow(f)

    >>> h=mmhistogram(f)

    >>> mmplot([[h]],[['style', 'impulses']])

f | [[h]],[['style', 'impulses']] |

## Equation

## Source Code

    def mmhistogram(f, option="uint16"):
        from Numeric import searchsorted, sort, ravel, concatenate, product
        n = searchsorted(sort(ravel(f)), range(max(ravel(f))+1))
        n = concatenate([n, [product(f.shape)]])
        h = n[1:]-n[:-1]
        return h

## See also

mmstats | Find global image statistics.
mmblob | Blob measurements from a labeled image.
mmgrain | Gray-scale statistics for each labeled region.
mmfreedom | Control automatic data type conversion.

[`mmwatershed`] [Up] [`mmlabel`] |
Copyright (c) 2003, Roberto A. Lotufo, UNICAMP-University of Campinas; Rubens C. Machado, CenPRA-Renato Archer Research Center.