Generalized Hard Constraints for Graph Segmentation

• 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.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

Image analysis

Bildanalys

Datoriserad bildanalys

Computerized Image Analysis

Computerized Image Processing

Datoriserad bildbehandling

Publikations- och innehållstyp

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