In this article we will see how we can histogram of the image in mahotas. An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. It plots the number of pixels for each tonal value. By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance.
In this tutorial we will use “lena” image, below is the command to load it.
Below is the lena image
In order to do this we will use
Syntax : mahotas.fullhistogram(img)
Argument : It takes image object as argument
Return : It returns ndarray of type np.uint32
Note : Input image should be filtered or should be loaded as grey
In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this
image = image[:, :, 0]
Below is the implementation
(array([82., 50., 34., 21., 24., 16., 9., 6., 9., 5.]), array([ 0., 391.9, 783.8, 1175.7, 1567.6, 1959.5, 2351.4, 2743.3, 3135.2, 3527.1, 3919. ]), a list of 10 Patch objects)
(array([27., 29., 56., 20., 23., 41., 21., 23., 10., 6.]), array([1.0000e+00, 4.4780e+02, 8.9460e+02, 1.3414e+03, 1.7882e+03, 2.2350e+03, 2.6818e+03, 3.1286e+03, 3.5754e+03, 4.0222e+03, 4.4690e+03]), a list of 10 Patch objects>
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