.png){kind=icon}
.png){kind=icon}
Return
Parallel connected-Component-Labeling based on homotopy trees
.png){kind=icon}
OA
AI
DOI：10.1016/j.patrec.2019.11.039.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Taking advantage of the topological and isotopic properties of binary digital images, we present here a new algorithm for connected component labeling (CLL). A local-to-global treatment of the topological information within the image, allows us to develop an inherent parallel approach. The time complexity order for an image of m x n pixels, under the assumption that a processing element exists for each pixel, is near O(log(m + n). Additionally, our method computes both the foreground and background CCL, and allows a straightforward computation of topological features like Adjacency Trees. Experiments show that our method obtains better performance metrics than other approaches. Our work aims at generating a new class of labeling algorithms: those centered in fully parallel approaches based on computational topology, thus allowing a perfect concurrent execution in multiple threads and preventing the use of critical sections and atomic instructions. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Connected-Component-Labeling
Computational topology
Adjacency tree
Digital image
Parallelism
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.3
Papers:
7.9K
Citations:
1.6W