Paper Info
Title
Parallel Light Speed Labeling: an efficient connected component algorithm for labeling and analysis on multi-core processors.
Abstract
In the last decade, many papers have been published to present sequential connected component labeling (CCL) algorithms. As modern processors are multi-core and tend to many cores, designing a CCL algorithm should address parallelism and multithreading. After a review of sequential CCL algorithms and a study of their variations, this paper presents the parallel version of the Light Speed Labeling for connected component analysis (CCA) and compares it to our parallelized implementations of State-of-the-Art sequential algorithms. We provide some benchmarks that help to figure out the intrinsic differences between these parallel algorithms. We show that thanks to its run-based processing, the LSL is intrinsically more efficient and faster than all pixel-based algorithms. We show also, that all the pixel-based are memory-bound on multi-socket machines and so are inefficient and do not scale, whereas LSL, thanks to its RLE compression can scale on such high-end machines. On a 4 × 15-core machine, and for 8192 × 8192 images, LSL outperforms its best competitor by a factor ×10.8 and achieves a throughput of 42.4 gigapixel labeled per second.
Year
DOI
Venue
2018
10.1007/s11554-016-0574-2
J. Real-Time Image Processing
Keywords
Field
DocType
Image processing, Computer vision, Connected component labeling, Connected Component analysis, Multi-core processor, Multithreading parallel processing
Multithreading,Parallel algorithm,Computer science,Parallel computing,Image processing,Algorithm,Real-time computing,Connected component,Pixel,Throughput,Connected-component labeling,Multi-core processor
Journal
Volume
Issue
ISSN
15
1
1861-8219
Citations 
PageRank 
References 
4
0.46
15
Authors
3
Name
Order
Citations
PageRank
Laurent Cabaret1172.57
Lionel Lacassagne212723.17
Daniel Etiemble330042.43