Graph Cuts, Caveat Utilitor, and Euler's Bridges of Konigsberg
University of Pennsylvania
| Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1503 |
Published in The Insight Journal - 2008 July - December.
Submitted by Nick Tustison on 11-15-2008.
Graph-based algorithms have enjoyed renewed interest for solving computer vision problems. These algorithms have been the subject of intense interest and research. In order to maintain the ITK library au courant, we developed a framework for graph-based methods of energy minimization in ITK which employ energy functions derived within a Markov Random Field (MRF) context. This required not only the implementation of the energy minimization methodology but also the more general requirement of introducing graph-related data structures into ITK which can be used for other graph-based algorithms pertinent to future extensions of the ITK library.
Please note that some of the algorithms described in this paper may be covered by patents and, as such, it is incumbent upon the user to seek licenses before building the binaries which utilize this code. Also note that “research use” is not exempt from acquiring such licenses. The only exemption from patent restrictions is “. . . amusement, to satisfy idle curiosity, or for strictly philosophical inquiry.”
Please note that some of the algorithms described in this paper may be covered by patents and, as such, it is incumbent upon the user to seek licenses before building the binaries which utilize this code. Also note that “research use” is not exempt from acquiring such licenses. The only exemption from patent restrictions is “. . . amusement, to satisfy idle curiosity, or for strictly philosophical inquiry.”
Code
Reviews
Good Contribution
by Subrahmanyam Gorthi on 2008-11-19 10:43:56 for revision #1 
expertise: 2 sensitivity: 5 
Summary:
The authors presented ITK implementation of the basic data structures for handling the graph cut problems, along with the Boykov alpha-expansion algorithm.They provided 2-D and 3-D examples of segmentation using the graph cuts algorithm. This is a significant contribution to ITK in the area of computer vision.
Hypothesis:Not Applicable.
Evidence:2-D and 3-D segmentation examples are given.
Appropriate references are given.
Open Science:This submission conformed to all my expectations of open science.i.e.,
- The authors provided the source code of their implementation.
- They provided the input images that they used.
- They provided enough details to be able to replicate their work.
The code is easy to read and the necessary documentation is provided.
Interest:The data structures and algorithms presented are general. Hence, they can be applied to a wide range of problems in computer vision.
Free comment :This is a significant contribution to ITK.
Minor comments:
- The phrase: "Caveat Utilitor", which is present in the paper title, is nowhere else mentioned in the paper. A brief description of it will be helpful.
- It seems there are two mismatches between the file-names mentioned in the paper, and the actual file-names in the "Source" directory. (i) In Page number:5 of the paper, under the "Testing" heading, a file with the name: "itkBoykovAlphaExpansionFilterTest.cxx" is mentioned. But, that file is not present in the "Source directory" of the code. (ii) Same is with the file-name under the "Examples" heading.
- It will be nice if the approximate times taken for segmentation of the images considered in the paper can be tabulated. Although they are not very exact, they can give a feel of approx. time taken, to the reader.
Thank you very much for this wonderful contribution.
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| Paper Id: | 306 |
| Categories: | Data Representation, Segmentation |
| Keywords: | Graph Cuts, Graphs, Min-Cut, Max Flow, Graph Data Structure, |
| Toolkit: | ITK |
| Revision: | 1 (11-15-2008) |
| Status: | Open for public review |
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| Full download: | .zip |
| Paper: | view, .pdf |
| Source code : | Download |
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