Accelerating Euler characteristic analysis: A multiprocessing approach with Octo-Voxel patterns and discrete chunk extraction
César Eduardo Muñoz-Chávez, Hermilo Sánchez-Cruz · Software Impacts · 2024
We present a new library designed to simplify the analysis of Euler characteristics. This program addresses the difficulties involved in generating 3D test objects and the complexities of extracting Octo-Voxel patterns. The library uses a novel method to rapidly generate data and extract descriptors by using effective multiprocessing. Furthermore, we have developed a method for extracting discrete CHUNKS from an image, allowing for separate multiprocessing assessment. This method accelerates the process of combination extraction and offers researchers a quick and effective way to explore Euler characteristics in a variety of applications. • Development of an algorithm using multiprocessing to speed up 3D voxelized object manipulation. • Extracting shape descriptors from 3D voxelized objects. • Vectorization analysis allow us to speed up processing time while using the Python language. • High reduction on processing time to handle 3D voxelized objects is achieved.