Actas de congresos
Laplacian coordinates for seeded image segmentation
Date
2014-06-23Registration in:
IEEE Conference on Computer Vision and Pattern Recognition, 27, 2014, Columbus, Ohio.
1063-6919
Author
Casaca, Wallace Correa de Oliveira
Nonato, Luis Gustavo
Taubin, Gabriel
Institutions
Abstract
Seed-based image segmentation methods have gained
much attention lately, mainly due to their good performance
in segmenting complex images with little user interaction.
Such popularity leveraged the development of many new
variations of seed-based image segmentation techniques,
which vary greatly regarding mathematical formulation and
complexity. Most existing methods in fact rely on complex
mathematical formulations that typically do not guarantee
unique solution for the segmentation problem while still being
prone to be trapped in local minima. In this work we
present a novel framework for seed-based image segmentation
that is mathematically simple, easy to implement, and
guaranteed to produce a unique solution. Moreover, the formulation
holds an anisotropic behavior, that is, pixels sharing
similar attributes are kept closer to each other while
big jumps are naturally imposed on the boundary between
image regions, thus ensuring better fitting on object boundaries.
We show that the proposed framework outperform
state-of-the-art techniques in terms of quantitative quality
metrics as well as qualitative visual results