Citrus yellow mite image recognition based on BP neural network

BP neural network has strong fault tolerance and adaptive learning ability, it is widely used in the field of digital image recognition. This paper, aiming at the problem of the citrus Eotetranychus automatic identification, using extraction methods based on the morphological features of the skeleto...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Huanliang Xiong, Canghai Wu, Qiangqiang Zhou
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:BP neural network has strong fault tolerance and adaptive learning ability, it is widely used in the field of digital image recognition. This paper, aiming at the problem of the citrus Eotetranychus automatic identification, using extraction methods based on the morphological features of the skeleton, automatically extracted citrus Eotetranychus's skeleton mathematical morphological characteristics, which were used as BP neural network input factors, achieved citrus Eotetranychus identification better.
DOI:10.1109/ICCSNT.2012.6526359