Communications of the ACM - Special issue on parallelism
Associative Nets: A Graph-Based Parallel Computing Model
IEEE Transactions on Computers
Shape Preservation in Morphological Filtering and Segmentation
SIBGRAPI '99 Proceedings of the XII Brazilian Symposium on Computer Graphics and Image Processing
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Connected Component Support for Image Analysis Programs
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Three-Dimensional MR Brain Segmentation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
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The role of connected components and connected filters is well established. In this paper a new segmentation procedure is presented based on connected components and connected filters. The use of connected components simplified the development of the algorithm. Moreover, if connected components are available as a basic data type, implementation is achievable without resorting to pixel level processing. Using parallel platforms with hardware support for connected components, the algorithm can fully exploit its data parallel implementation. We apply our segmentation procedure to axially oriented magnetic resonance brain images. Novel ideas are presented of how connected components operations (e.g. moments and bounding boxes) and connected filtering (e.g. area close-opening) can be effectively used together.