TY - GEN
T1 - Intelligent System to Evaluate the Quality of Orange, Lemon, Sweet Lime and Tomato Using Back-Propagation Neural-Network (BPNN) and Probabilistic Neural Network (PNN)
AU - Narendra, V. G.
AU - Govardhan Hegde, K.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - The quality assessment and sorting millions of fruits as well as vegetables by manual is usually slower. But also costly and cannot give an accurate result. In this research, to increase the quality of food above products were developed by using a vision-based quality inspection and sorting system. The quality assessment and sorting process analyzes taken image for its quality (good). It discards the defected one (bad). The image can be of vegetables or fruits. Four different systems for different food products (Orange, Lemon, Sweet Lime, and Tomato) have been developed. We have used a dataset of one thousand two hundred images which can be used to train as well as test the image systems. All images of 300 in the count. The obtained overall accuracy ranges between 85.0% to 95.00% for Orange, Lemon, Sweet Lime, and Tomato by using soft-computing techniques such as Backpropagation neural network and Probabilistic neural network.
AB - The quality assessment and sorting millions of fruits as well as vegetables by manual is usually slower. But also costly and cannot give an accurate result. In this research, to increase the quality of food above products were developed by using a vision-based quality inspection and sorting system. The quality assessment and sorting process analyzes taken image for its quality (good). It discards the defected one (bad). The image can be of vegetables or fruits. Four different systems for different food products (Orange, Lemon, Sweet Lime, and Tomato) have been developed. We have used a dataset of one thousand two hundred images which can be used to train as well as test the image systems. All images of 300 in the count. The obtained overall accuracy ranges between 85.0% to 95.00% for Orange, Lemon, Sweet Lime, and Tomato by using soft-computing techniques such as Backpropagation neural network and Probabilistic neural network.
UR - http://www.scopus.com/inward/record.url?scp=85075249966&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075249966&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-0108-1_34
DO - 10.1007/978-981-15-0108-1_34
M3 - Conference contribution
AN - SCOPUS:85075249966
SN - 9789811501074
T3 - Communications in Computer and Information Science
SP - 369
EP - 382
BT - Advanced Informatics for Computing Research - 3rd International Conference, ICAICR 2019, Revised Selected Papers
A2 - Luhach, Ashish Kumar
A2 - Jat, Dharm Singh
A2 - Hawari, Kamarul Bin Ghazali
A2 - Gao, Xiao-Zhi
A2 - Lingras, Pawan
PB - Springer Paris
T2 - 3rd International Conference on Advanced Informatics for Computing Research, ICAICR 2019
Y2 - 15 June 2019 through 16 June 2019
ER -