Mathematical Model for Image Processing Using Graph Theory
Rajshree Dahal, Ritwika Das Gupta, Debabrata Samanta · Advances in healthcare information systems and administration book series · 2022
Image segmentation being an important aspect of computer systems, graph theory provides the most elemental way of representing various parts of an image into mathematical structures. There are many applications of image segmentations including face recognition systems, remote sensing, detecting images sent by satellites, optometry, medical image reading, and many more. Bi-partite graphs are useful in determination of cuts in the segmentation process. These structures are analysed by considering each vertex as pixel, and each weight is some aspect of dissimilarity for two vertices connected by an edge with weights. This makes the problem-solving part very flexible, and their computation becomes easy and fast. The problem is usually parted into small subgraphs that are bound under some continuous forms of graphs like spanning trees, cut vertices or edges, shortest paths graphs, and so on. The cluster formation is proved to be one of most commonly used methods in image segmentation.