Application of Artificial Intelligence and Computer Vision for Measuring and Counting Oysters

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:30:03Z
Fecha de publicación2025-01-01
ResumenOne of the most important activities in any oyster farm is the measurement of oyster size; this activity is time-consuming and conducted manually, generally using a caliper, which leads to high measurement variability. This paper proposes a methodology to count and obtain the length and width averages of a sample of oysters from an image, relying on artificial intelligence (AI), which refers to systems capable of learning and decision-making, and computer vision (CV), which enables the extraction of information from digital images. The proposed approach employs the DBScan clustering algorithm, an artificial neural network (ANN), and a random forest classifier to enable automatic oyster classification, counting, and size estimation from images. As a result of the proposed methodology, the speed in measuring the length and width of the oysters was 86.7 times faster than manual measurement. Regarding the counting, the process missed the total count of oysters in two of the ten images. These results demonstrate the feasibility of using the proposed methodology to measure oyster size and count in oyster farms.es_ES
Doihttps://doi.org/10.3390/jimaging11120439es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/2015
Idiomaeses_ES
EditorialMDPI AGes_ES
RelaciónJournal of Imaginges_ES
URL relacionadohttps://doi.org/10.3390/jimaging11120439es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteJournal of Imaging
TítuloApplication of Artificial Intelligence and Computer Vision for Measuring and Counting Oysterses_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorPino, Julio Antonio Laria
AutorVillanueva, Jesús David Terán
AutorMenchaca, Julio Laria
AutorSolorio, Leobardo Garcia
AutorMartínez, Salvador Ibarra
AutorFlores, Mirna Patricia Ponce
AutorPineda, Aurelio Alejandro Santiago
AutorPino, Julio Antonio Lariaes_ES
AutorVillanueva, Jesús David Teránes_ES
AutorMenchaca, Julio Lariaes_ES
AutorSolorio, Leobardo Garciaes_ES
AutorMartínez, Salvador Ibarraes_ES
AutorFlores, Mirna Patricia Poncees_ES
AutorPineda, Aurelio Alejandro Santiagoes_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número12es_ES
Rango de páginas439es_ES
URL relacionadahttps://doi.org/10.3390/jimaging11120439
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen11es_ES

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