TY - GEN
T1 - Date fruit sorting using appearance-based information and neural network classifier
AU - Bouchech, H.
AU - Foufou, S.
AU - Khriji, L.
PY - 2014/10/22
Y1 - 2014/10/22
N2 - This paper presents a new two-step system for automatically sorting date fruit in four categories which are big 'Sukkari' dates, defective big 'Sukkari' dates, small 'Sukkari' dates and 'Khalas' dates. In the first step, we used the Principal Component Analysis tool for feature extraction and data dimensionality reduction. Then, the obtained features were injected in a modified Back-Propagation-based Neural Network to be classified. Four tests were made upon a locally made database of date images, and obtained results varied between 96 and 100% accuracy.
AB - This paper presents a new two-step system for automatically sorting date fruit in four categories which are big 'Sukkari' dates, defective big 'Sukkari' dates, small 'Sukkari' dates and 'Khalas' dates. In the first step, we used the Principal Component Analysis tool for feature extraction and data dimensionality reduction. Then, the obtained features were injected in a modified Back-Propagation-based Neural Network to be classified. Four tests were made upon a locally made database of date images, and obtained results varied between 96 and 100% accuracy.
KW - Date fruit
KW - Neural network
KW - Principal component analysis
UR - http://www.scopus.com/inward/record.url?scp=84984633388&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84984633388&partnerID=8YFLogxK
U2 - 10.17660/ActaHortic.2014.1054.32
DO - 10.17660/ActaHortic.2014.1054.32
M3 - Conference contribution
AN - SCOPUS:84984633388
VL - 1054
T3 - Acta Horticulturae
SP - 271
EP - 278
BT - International Conference on Agricultural Engineering
PB - International Society for Horticultural Science
ER -