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fast morphology using kernel subdivision

Project description

[license GPL] [versions] [downloads] [documentation]

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Description

This module enables efficient morphological erosion and dilatation. It uses the kernel subdivision algorithm implemented in C, with multithreading.

Example of kernel decomposition

Features

  1. Works for any tensor dimension, 2d for images, 3d for videos…

  2. The morphological structuring element decomposition logarithmically reduces temporal complexity.

  3. Functions can be parallelized to take advantage of all the CPU threads, in exchange of higher edge effects.

  4. Functions can be compiled dynamically in C to reduce side-effects and overhead, in exchange for a longer loading time.

Examples

import morphomath
import numpy as np

kernel = morphomath.Kernel([[1, 1], [0, 1]])

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