Generalized Hard Constraints for Graph Segmentation
2011 (English)In: Image Analysis, 17th Scandinavian Conference. SCIA 2011., Springer , 2011Conference paper (Refereed)
Graph-based methods have become well-established tools for image segmentation. Viewing the image as a weighted graph, these methods seek to extract a graph cut that best matches the image content.Many of these methods are interactive, in that they allow a human operator to guide the segmentation process by specifying a set of hard constraints that the cut must satisfy. Typically, these constraints are given in one of two forms: regional constraints (a set of vertices that must be separated by the cut) or boundary constraints (a set of edges that must be included in the cut). Here, we propose a new type of hard constraints,that includes both regional constraints and boundary constraints as special cases. We also present an efficient method for computing cuts that satisfy a set of generalized constraints, while globally minimizing a graph-cut measure.
Place, publisher, year, edition, pages
Springer , 2011.
, Lecture Notes in Computer Science
Computer Vision and Robotics (Autonomous Systems)
Research subject Computerized Image Analysis; Computerized Image Processing
IdentifiersURN: urn:nbn:se:uu:diva-149259OAI: oai:DiVA.org:uu-149259DiVA: diva2:404332