In this article we will see how we can get regional minima of image in mahotas. Regional minima is a stricter criterion than the local minima as it takes the whole object into account and not just the neighborhood. Minima are connected components of pixels with a constant intensity value, surrounded by pixels with a highr value.
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.regmin(img)
Argument : It takes image object 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
- Mahotas - Regional Maxima of Image
- Mahotas - Local Minima in Image
- Mahotas - Labelled Image from the Normal Image
- Mahotas - Reconstructing image from transformed Daubechies wavelet image
- Mahotas - Getting Mean Value of Image
- Mahotas - Element Structure for Eroding Image
- Mahotas - Dilating Image
- Mahotas - Eroding Image
- Mahotas - Opening Process on Image
- Mahotas - Element Structure for Dilating Image
- Loading Image using Mahotas - Python
- Mahotas - Transforming image using Daubechies wavelet
- Mahotas - Removing border effect from Wavelet Center Image
- Mahotas - Cropping Image
- Mahotas - Fraction of zeros in image
- Mahotas - Making Image Wavelet Center
- Mahotas - Perimeter of Objects in binary image
- Mahotas - Loading image as grey
- Mahotas - Getting Bounding Boxes of Labelled Image
- Mahotas - Distance from binary image
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