In this article we will see how we can the image moments in mahotas. In image processing, computer vision and related fields, an image moment is a certain particular weighted average of the image pixels’ intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation.
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 mahotas.moments method
Syntax : mahotas.moments(img, p0, p1)
Argument : It takes image object and two float values as argument
Return : It returns image object
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
Moment value = 6.784986531904299e+35
Moment value = 1.5229432312149368e+42
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