Mahotas - Riddler-Calvard Method

In this article, we will see how we can implement riddler calvard method in mahotas. This is alternative of otsu's method. The Riddler and Calvard algorithm uses an iterative clustering approach. First a initial estimate of the threshold is to be made (e.g. mean image intensity). Pixels above and below the threshold are assigned to the object and background classes respectively.

In this tutorial we will use "luispedro" image, below is the command to load it. 

mahotas.demos.load('luispedro')

Below is the luispedro image 

👁 Image

In order to do this we will use mahotas.rc method  

Syntax : mahotas.rc(image)
Argument : It takes image object as argument
Return : It returns numpy.float64 
 

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]

Example 1: 

Output : 
 

👁 Image

Example 2: 

Output : 

👁 Image