A new approach for automated image segmentation based on unit-linking PCNN

Abstract

The PCNN (pulse coupled neural network), an artificial neural network based on biology, can be efficiently applied to image segmentation. The performance of image segmentation based on PCNN depends on suitable PCNN parameters. However, it is difficult to get suitable PCNN parameters for different kinds of images because different kinds of images have different suitable PCNN parameters. So far, no paper has described how to get the suitable PCNN parameters to efficiently segment images. In this paper, we put forward a new approach for image segmentation based on a unit-linking PCNN, by which we can use the same PCNN parameter to efficiently segment different kinds of images. Therefore, using this new approach can automatically and efficiently segment images without choosing different parameters for different kinds of images.