The recent advances in research on physics, computing, medicine and others, require the use of certain shape characterization parameters, especially for morphological analysis. The most known morphometric characteristics are: the perimeter, the diameter, the circularity, the tortuosity, the compactness factor and others. In this paper we propose a new parallel algorithm for the diameter determination of multi-level image in Ө(1) time, intended for a parallel Reconfigurable Mesh Computer (RMC) machine of n x n Elementary Processors 1098 Mohammed Khaldoun et al. (PEs). The algorithm consists in determining the maximum diameter of each component of a 2D multilevel image. The approach used involves only the points of the contour of each component of the image. This allowed us to apply this approach on a multi-level image. Using the Ө (1) time Min / Max algorithm, we have been able to reduce the complexity of our algorithm to Ө (1) time.
Algorithms are commonly perceived as difficult subjects. Many applications today require complex algorithms. However, the researchers look for ways to make them as simple as possible. In high time demanding fields, the process of sorting represents one of the foremost issues in the data structure for searching and optimization algorithms. In parallel processing, we divide program instructions among multiple processors by breaking problems into modules that can be executed in parallel, to reduce the execution time. In this paper, we proposed a novel parallel, re-configurable and adaptive sorting network of the BulkSort algorithm. Our architecture is based on simple and elementary operations such as comparison and binary shifting. The main strength of the proposed solution is the ability to sort in parallel without memory usage. Experimental results show that our proposed model is promising according to the required resources and its ability to perform a high-speed sorting process. In this study, we take into account the analysis result of the Simulink design to establish the required hardware resources of the proposed system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.