Constrained Connectivity and Transition Regions
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Advances in constrained connectivity
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Preventing chaining through transitions while favouring it within homogeneous regions
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Pattern spectra from partition pyramids and hierarchies
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Frequent and dependent connectivities
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Spatio-temporal quasi-flat zones for morphological video segmentation
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Fast quasi-flat zones filtering using area threshold and region merging
Journal of Visual Communication and Image Representation
Local Mutual Information for Dissimilarity-Based Image Segmentation
Journal of Mathematical Imaging and Vision
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This paper introduces a framework for the generation of genuine connectivity relations whose equivalent classes (called connected components) define unique partitions of the definition domain of a given grey tone image. This framework exploits the total ordering relation between the alpha-connected components of a pixel (two pixels are alpha-connected if there exists at least one path joining them such that the intensity differences between successive pixels of this path does not exceed a threshold value equal to alpha). Genuine connectivity relations are then obtained by considering the largest alpha-connected components satisfying one or more logical predicates such as the variance of the intensity values of the alpha-connected components not exceeding a given threshold value. Fine to coarse hiearchy partitions are generated by carefully varying the input threshold values. The proposed framework has the striking property of uniqueness. That is, the results do not depend on pixel processing order and are fully defined by the values of the threshold values, in contrast to most region growing procedures.