Variational and Level Set Methods in Image Segmentation

The book "Variational and Level Set Methods in Image Segmentation" offers a comprehensive examination of image segmentation through variational methods. It addresses the division of an image into significant regions that are important for various applications, including robotics, medical image analysis, and image database queries. The focus is on the use of closed regular level sets to define the segmentation regions, as well as the implementation of level set methods for active contour evolution. The authors, Amar Mitiche and Ismail Ben Ayed, develop the methods from an objective functional that considers both the partitioning of the image domain and the image data within the partitions. The book covers fundamental methods of two-region segmentation, multi-region extensions, region merging, and various modeling approaches, including parametric and non-parametric models. It is a valuable resource for professionals and students who wish to engage with the theoretical and practical aspects of image segmentation.