Literature Review for Counting Colony-Forming Units in Microorganisms Using Artificial Vision
DOI:
https://doi.org/10.18779/ingenio.v9i1.1117Keywords:
applied technology, artificial intelligence, image processing, bacterial cultures, automationAbstract
This study conducted a Systematic Literature Review with the aim of identifying the most efficient procedures for processing images used in microbiological analyses. This search includes publications from 2019 to 2025, using the main indexed scientific databases such as Scielo, ACM, Redalyc, Consensus, IEEE Xplore, and Springer, as well as the Google Scholar search engine. During the search, 41 articles were analyzed, identifying various approaches to traditional image processing, machine learning, and hybrid techniques. The results allowed us to identify methods and tools, providing a solid basis for their incorporation into a computer system. The main contribution is to establish the foundations for the development of an automated technological solution that facilitates the implementation of automatic counting to streamline the work of scientific and clinical laboratories by reducing time and human error.
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Copyright (c) 2026 Luis Alberto Jiménez Villa, María Salomé Alejandre Apolinar, Virginia Lagunes Barradas, Miguel Ángel Hidalgo Reyes
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