Efficient Component Labeling of Images of Arbitrary Dimension Represented by Linear Bintrees
IEEE Transactions on Pattern Analysis and Machine Intelligence
An EREW PRAM Algorithm for Image Component Labeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for Image Component Labeling on SIMD Mesh-Connected Computers
IEEE Transactions on Computers
Fast Image Labeling Using Local Operators on Mesh-Connected Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel Architectures and Algorithms for Image Component Labeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel algorithms for image histogramming and connected components with an experimental study
Journal of Parallel and Distributed Computing
The Journal of Supercomputing
Analyzing blood cell image to distinguish its abnormalities (poster session)
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Extracting regions of interest applying a local watershed transformation
Proceedings of the conference on Visualization '00
Extending the data parallel paradigm with data-dependent operators
Parallel Computing - Parallel computing in image and video processing
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Parallel Multiresolution Image Segmentation with Watershed Transformation
ParNum '99 Proceedings of the 4th International ACPC Conference Including Special Tracks on Parallel Numerics and Parallel Computing in Image Processing, Video Processing, and Multimedia: Parallel Computation
The Feature Tree: Visualizing Feature Tracking in Distributed AMR Datasets
PVG '03 Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics
An improved watershed algorithm based on efficient computation of shortest paths
Pattern Recognition
Image enhancement - An emergent pattern formation approach via decentralised multi-agent systems
Multiagent and Grid Systems - Special Issue on Nature inspired systems for parallel, asynchronous and decentralised environments
Watershed segmentation using prior shape and appearance knowledge
Image and Vision Computing
Parallel Volume Image Segmentation with Watershed Transformation
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Fast, parallel watershed algorithm based on path tracing
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part II
Improved watershed transform for tumor segmentation: Application to mammogram image compression
Expert Systems with Applications: An International Journal
Parallel computing of catchment basins in large digital elevation model
HPCA'09 Proceedings of the Second international conference on High Performance Computing and Applications
The Watershed Transform: Definitions, Algorithms and Parallelization Strategies
Fundamenta Informaticae
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The parallel watershed transformation used in gray scale image segmentation is reconsidered in this paper on the basis of the component labeling problem. The main idea is to break the sequentiality of the watershed transformation and to correctly delimit the extent of all connected components locally, on each processor, simultaneously. The internal fragmentation of the catchment basins, due to domain decomposition, into smaller subcomponents is ulteriorly solved by employing a global connected components operator. Therefore, in a pyramidal structure of master-slave processors, internal contours of adjacent subcomponents within the same component are hierarchically removed. Global final connected areas are efficiently obtained in log2N steps on a logical grid of N processors. Timings and segmentation results of the algorithm built on top of the Message Passing Interface (MPI) and tested on the Cray T3D are brought forward to justify the superiority of the novel design solution compared against previous implementations.