A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Short communication: An evaluation metric for image segmentation of multiple objects
Image and Vision Computing
Topology adaptive active membrane
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Fuzzy logic approaches to structure preserving dimensionality reduction
IEEE Transactions on Fuzzy Systems
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Segmentation of multiple objects in a scene from the single initialization of an active membrane is always advantageous compared to separate initialization of active contour for segmenting each of the multiple objects. This proposal, however, is not robust in segmenting poorly-contrasted touching objects especially when pixel groups belonging to a single object can have spectral signatures similar to the background pixels. In this paper we have used fuzzy rule based learning scheme to record the spectral signature of the objects and background and spatial information of the topology of an active membrane segmenting the objects. The learning scheme helps in splitting the active membrane for segmenting multiple objects and integrates the topology adaptive property of the active membrane with its architecture and evolution. The evolution of this membrane is tested in a challenging application domain of estimation of sizes of oil sand.