Automatic identification of species with neural networks.
A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.
Grupo de Ictiología, Instituto de Biología, Universidad de Antioquia , Medellín , Colombia ; Department of Biology, University of Puerto Rico-Río Piedras , San Juan, PR , USA.
Andrés
A
Hernández-Serna
Grupo de Ictiología, Instituto de Biología, Universidad de Antioquia , Medellín , Colombia.
Luz Fernanda
LF
Jiménez-Segura
Butterflies; Digital image; Feature extraction; Fish; Neural network; Plant; Species