Noshahri, EhsanAraújo, CristianoRodríguez, Álvaro2026-09-172026-09-172025Noshahri, E., Araujo, C. V., & Rodríguez, Á. (2026). Automated Counting of Zebrafish: An Image Processing Approach. In Proceedings XoveTIC 2025: Impulsando el talento científico (pp. 199-206). Servizo de Publicacións UDC. https://doi.org/10.17979/spu.23.c36978-84-9749-925-5https://hdl.handle.net/2183/49295Presentado en: VIII Congreso Xove TIC: impulsando el talento científico. Octubre, 2025, A Coruña.[Abstract] Accurate quantification of fish populations is a critical task in aquaculture and behavioral research. In this work, we present a lightweight image processing pipeline for the automatic counting of zebrafish (Danio rerio) in a multi-compartment aquatic system. The approach combines background subtraction, morphological refinement, and watershed segmentation to estimate fish counts directly from raw video without annotated training data. The method enables non-invasive and reproducible counting while remaining computationally efficient and interpretable. Although challenges remain under occlusion and limited visibility, the method reduces reliance on manual observation and demonstrates that classical image-processing techniques can provide efficient, interpretable, and accessible solutions for early-stage behavioral experiments.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Zebrafish countingImage processingWatershed segmentationBackground subtractionBehavioral researchconference outputopen access10.17979/spu.23.c36