Artículo
An image processing pipeline to segment iris for unconstrained cow identification system
Fecha de publicación:
01/2019
Editorial:
De Gruyter
Revista:
Open Computer Science
ISSN:
2299-1093
e-ISSN:
2299-1093
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
One of the most evident costs in cow farming is the identification of the animals. Classic identification processes are labour-intensive, prone to human errors and invasive for the animal. An automated alternative is an animal identification based on unique biometric patterns like iris recognition; in this context, correct segmentation of the region of interest becomes of critical importance. This work introduces a bovine iris segmentation pipeline that processes images taken in the wild, extracting the iris region. The solution deals with images taken with a regular visible-light camera in real scenarios, where reflections in the iris and camera flash introduce a high level of noise that makes the segmentation procedure challenging. Traditional segmentation techniques for the human iris are not applicable given the nature of the bovine eye; at this aim, a dataset composed of catalogued images and manually labelled ground truth data of Aberdeen-Angus has been used for the experiments and made publicly available. The unique ID number for each different animal in the dataset is provided, making it suitable for recognition tasks. Segmentation results have been validated with our dataset showing high reliability: with the most pessimistic metric (i.e. intersection over union), a mean score of 0.8957 has been obtained.
Palabras clave:
BOVINE EYE
,
IMAGE PROCESSING
,
IRIS SEGMENTATION
,
PUPIL SEGMENTATION
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Licencia
Identificadores
Colecciones
Articulos (ICIC)
Articulos de INSTITUTO DE CS. E INGENIERIA DE LA COMPUTACION
Articulos de INSTITUTO DE CS. E INGENIERIA DE LA COMPUTACION
Citación
Larregui, Juan Ignacio; Cazzato, Dario; Castro, Silvia Mabel; An image processing pipeline to segment iris for unconstrained cow identification system; De Gruyter; Open Computer Science; 9; 1; 1-2019; 145-159
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