Publication | Closed Access
Object segmentation using graph cuts based active contours
91
Citations
23
References
2005
Year
Unknown Venue
EngineeringObject SegmentationShape AnalysisComputer-aided DesignImage AnalysisActive ContoursPattern RecognitionEdge DetectionComputational GeometryGeometry ProcessingGeometric ModelingMachine VisionSegmentation ProblemsComputer ScienceMedical Image ComputingComputer VisionNatural SciencesGraph CutsShape ModelingImage Segmentation
In this paper we present a graph cuts based active contours (GCBAC) approach to object segmentation problems. Our method is a combination of active contours and the optimization tool of graph cuts and differs fundamentally from traditional active contours in that it uses graph cuts to iteratively deform the contour. Consequently, it has the following advantages. (1) It has the ability to jump over local minima and provide a more global result. (2) Graph cuts guarantee continuity and lead to smooth contours free of self-crossing and uneven spacing problems. Therefore, the internal force, which is commonly used in traditional energy functions to control the smoothness, is no longer needed, and hence the number of parameters is greatly reduced. (3). Our approach easily extends to the segmentation of three and higher dimensional objects. In addition, the algorithm is suitable for interactive correction and is shown to always converge. Experimental results and analyses are provided.
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