Finding Euler tours in parallel
Journal of Computer and System Sciences
Data movement techniques for the pyramid computer
SIAM Journal on Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hypercube and shuffle-exchange algorithms for image component labeling
Journal of Algorithms
Computing connected components on parallel computers
Communications of the ACM
Digital Picture Processing
The complexity of parallel computations
The complexity of parallel computations
Parallel computable contour based feature strings for 2-D shape recognition
Pattern Recognition Letters
Parallel Architectures and Algorithms for Image Component Labeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel Image Component Labeling With Watershed Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Theoretical Computer Science
C3L: A Chip for Connected Component Labeling
VLSID '97 Proceedings of the Tenth International Conference on VLSI Design: VLSI in Multimedia Applications
Real-Time Object-Based Video Segmentation Using Colour Segmentation and Connected Component Labeling
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
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An important midlevel task for computer vision is addressed. The problem consists of labeling connected components in N/sup 1/2/*N/sup 2/2/ binary images. This task can be solved with parallel computers by using a simple and novel algorithm. The parallel computing model used is a synchronous fine-grained shared-memory model where only one processor can read from or write to the same memory location at a given time. This model is known as the exclusive-read exclusive-write parallel RAM (EREW PRAM). Using this model, the algorithm presented has O(log N) complexity. The algorithm can run on parallel machines other than the EREW PRAM. In particular, it offers an optimal image component labeling algorithm for mesh-connected computers.