Image segmentation based on PCNN impulse neural network and region growing algorithm

Image segmentation based on PCNN impulse neural network and region growing algorithm

Image segmentation is an important task in the field of computer vision, which aims to divide images into different regions with similar characteristics. In this article, we will introduce how to use PCNN spiking neural network combined with the region growing algorithm to achieve image segmentation. We will also provide corresponding MATLAB code to help readers implement this process.

PCNN (Pulse-Coupled Neural Network) is a biologically inspired neural network model that simulates the interaction between neurons in the biological nervous system. PCNN can effectively extract edge and texture features in images by simulating the propagation and coupling process of pulses. The region growing algorithm is an image segmentation method based on pixel similarity. It starts from seed pixels and gradually grows regions by comparing similarities with neighboring pixels.

The following is the MATLAB code that uses PCNN pulse neural network combined with region growing algorithm to achieve image segmentation:

% 读取输入图像
image = imread('input_image.jpg');

% 初始化PCNN参数
alpha = 0.1;