Abstract:
Level set models are extensively used for image segmentation because of their capability to handle topological changes. In this paper, the proposed model uses combined lo...Show MoreMetadata
Abstract:
Level set models are extensively used for image segmentation because of their capability to handle topological changes. In this paper, the proposed model uses combined local image information and global image information to evolve the con-tour around the object boundary, making it robust, irrespective of the inhomogeneity. The proposed model is capable to deal with bias conditions, such as intensity inhomogeneity and light effects. We test this model on synthetic, and real images, confirming its superiority over previous models.
Published in: 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
Date of Conference: 16-19 November 2021
Date Added to IEEE Xplore: 28 December 2021
ISBN Information: