The Region-based Image Segmentation Under Membrane Computing

Image segmentation is one of the most important issues in digital image processing and computer vision. The purpose of segmenting an image is to use these regions to recognize and analyze the image. The region-based segmentation is a common image segmentation method.Membrane computing, as a new natural computing, is a novel class of computing models inspired by the structure and functioning of living cells as well as from the cooperation between cells in tissues and organs. The computing system using this model is called a membrane system or a P system. P systems with the advantages of distributed parallel computing and non-determinism have been applied to different fields. This paper focuses on the application of P system to image segmentation.Based on the mechanism of tissue-like P system and its parallel computing advantages, this paper discussed the region-based image segmentation methods under P system. The main innovations are shown as follows:(1) A region-based gray image segmentation method under P system was proposed. We designed a tissue-like P system with symport/antiport rules. It used evolution rules and communication rules to achieve an adaptive region growing for gray image segmentation. This method was compared with traditional region segmentation method and the comparison results demonstrate the effectiveness and feasibility of the proposed method.(2) A region-based color image segmentation method under P system was proposed. A tissue-like P system achieved an adaptive selection of target regions with the specially designed membrane objects, structure and rules. The proposed method was compared with the existing region segmentation method on several real-life color images.