International audienceIn 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

Until recent years, labeling algorithms for GPUs have been iterative. This was a major problem because the computation time depended on the content of the image. The number of iterations to reach the stability of labels propagation could be very high. In the last years, new direct labeling algorithms have been proposed. They add some extra tests to avoid memory accesses and serialization due to atomic instructions. This article presents two new algorithms, one for labeling (CCL) and one for analysis (CCA). These algorithms use a new data structure combined with low-level intrinsics to leverage the architecture. The connected component analysis algorithm can efficiently compute features like bounding rectangles or statistical moments. A benchmark on a Jetson TX2 shows that the labeling algorithm is from 1.8 up to 2.7 times faster than the State-of-the-Art and can reach a processing rate of 200 fps for a resolution of 2048×2048.