title: A nonconservative flow field for robust variational image segmentation.
abstract: We introduce a robust image segmentation method based on a variational formulation using edge flow vectors. We demonstrate the nonconservative nature of this flow field, a feature that helps in a better segmentation of objects with concavities. A multiscale version of this method is developed and is shown to improve the localization of the object boundaries. We compare and contrast the proposed method with well known state-of-the-art methods. Detailed experimental results are provided on both synthetic and natural images that demonstrate that the proposed approach is quite competitive.
authors.affiliation: Vision and ResearchLaboratory, Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, 93106, USA. pratim@ece.ucsb.edu
authors.forename: Pratim
authors.initials: P
authors.lastname: Ghosh
authors.forename: Luca
authors.initials: L
authors.lastname: Bertelli
authors.forename: Baris
authors.initials: B
authors.lastname: Sumengen
authors.forename: B S
authors.initials: BS
authors.lastname: Manjunath