Connected component labeling (CCL) is a mandatory step in image segmentation where each object in an image is identified and uniquely labeled. Sequential CCL is a time-consuming operation and thus is often implemented within parallel processing framework to reduce execution time. Several parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZLE) meth...

the offered approach is based on the establishment of the functional dependence between river water discharge (q) and suspended ms ,in a number of observations, which noticeably differs from the mean value (r) of subsequent allocated period(s). the earliest period anthropogenic component during the subsequent period(s) is the difference between an actual suspended sediment yield and its hypothe...

Let M be a connected sum of finitely many lens spaces, and let N be a connected sum of finitely many copies of S × S. We show that there is a uniruled algebraic variety X such that the connected sum M#N of M and N is diffeomorphic to a connected component of the set of real points X(R) of X. In particular, any finite connected sum of lens spaces is diffeomorphic to a real component of a unirule...

In this paper, we present an on-line full dynamic algorithm for maintaining strongly connected component of a directed graph in a shared memory architecture. The edges and vertices are added or deleted concurrently by fixed number of threads. To the the best of our knowledge, this is the first work to propose using linearizable concurrent directed graph and is build using both ordered and unord...

A new approach for segmenting 3D voxel data sets is presented. It is semi-automatic and consists of two phases. First, the initial segmentation is accomplished by voxel labeling using statistical maximum likelihood estimation techniques. The novelty of the present approach is that the type probability distribution function is not required a priori. A multi-parameter distribution which includes ...

Connected component labeling is a process that assigns unique labels to the connected components of a binary image. The main contribution of this paper is to present a low-latency hardware connected component labeling algorithm for k-concave binary images designed and implemented in FPGA. Pixels of a binary image are given to the FPGA in raster order, and the resulting labels are also output in...

Connected component labeling is a key step in a wide-range of applications, such as community detection in social networks and coherent structure identification in massivelyparallel scientific simulations. There have been several distributed-memory connected component algorithms described in literature; however, little has been done regarding their scalability analysis. Theoretical and experime...

Recent success in wavelet image coding is mainly attributed to a recognition of the importance of data organization and representation. There have been several very competitive wavelet coders developed, namely, Shapiro's (1993) embedded zerotree wavelets (EZW), Servetto et al.'s (1995) morphological representation of wavelet data (MRWD), and Said and Pearlman's (see IEEE Trans. Circuits Syst. V...

In this paper we consider the problem of labeling the connected components of a binary image. We descnbe three different algorithms and variations thereof which we implemented on NASA's MPP. These algoritluns include a simple label propagation algorithm. a version of Levialdi's algorithm, and an asymptotically optimal divide-and-eonquer algorithm. We discuss the perfonnance of these algorithms ...

We describe a highly scalable algorithm for computing connected components in large binary 3D grids. We employ a streaming version of the union-find algorithm that—as it processes the voxel grid row-by-row and layer-by-layer—only maintains the component structure along a single layer of active rows. We can process voxel grids whose sizes are three orders of magnitude larger than what the best p...