# The algorithm of formation of a training set for an artificial neural network for image segmentation

## TL;DR

This paper introduces a novel algorithm for creating training sets for neural networks in image segmentation, utilizing only one image and region growing, with noise-based training data generation.

## Contribution

It proposes a unique training set formation method using a single image and noise, combined with a three-layer perceptron for segmentation.

## Key findings

- Effective segmentation with a single image demonstrated
- Noise-based training set generation proved successful
- Method tested in automatic and interactive modes

## Abstract

This article suggests an algorithm of formation a training set for artificial neural network in case of image segmentation. The distinctive feature of this algorithm is that it using only one image for segmentation. The segmentation performs using three-layer perceptron. The main method of the segmentation is a method of region growing. Neural network is using for get a decision to include pixel into an area or not. Impulse noise is using for generation of a training set. Pixels damaged by noise are not related to the same region. Suggested method has been tested with help of computer experiment in automatic and interactive modes.