期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 21, 期 8, 页码 3531-3545出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2012.2192129
关键词
Connected component; deconvolution; digital topology; discrete level set; energy-based segmentation; multiregion segmentation; region competition; topological constraint
资金
- Swiss Federal Commission for Technology and Innovation [9325.2-PFLS-LS]
- Bitplane, Inc.
- Swiss SystemsX.ch Initiative [LipidX, WingX]
We present a discrete unsupervised multiregion-competition algorithm for image segmentation over different energy functionals. The number of regions present in an image does not need to be known a priori, nor their photometric properties. The algorithm jointly estimates the number of regions, their photometries, and their contours. The required regularization is provided by defining a region as a connected set of pixels. The evolving contours in the image are represented by computational particles that move as driven by an energy-minimization algorithm. We present an efficient discrete algorithm that allows minimizing a range of well-known energy functionals under the topological constraint of regions being connected components. The presented framework and algorithms are implemented in the open-source Insight Toolkit image-processing library.
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