Wheat Seeds Classification using Multi-Layer Perceptron Artificial Neural Network

Nabeel Ali Abdullah; Dr. Anas M. Quteishat

Wheat seeds classification is an important agriculture process. In this paper a wheat classification system based on Artificial Neural Network (ANN) is presented. The proposed system aims to classify three different wheat seeds into their corresponding classes. The system consisted of two stages. In the first stage image processing is applied on the obtain images and important geometrical features are extracted. In the second stage the extracted features are fed in to a Multi-layer Perceptron (MLP) neural network trained using back propagation learning algorithm. Three experiments were conducted; the first experiment using all the data, the second experiment using noisy data, and the final experiment using part of the training data. The empirical results show that the proposed classification system was able to classify the wheat seeds with a testing accuracy of around 95%.

Select Volume / Issues:

• Volume 6 Issue 2, Mar. 2015

Year:

2015

Type of Publication:

Article

Keywords:

Wheat Classification; Neural Networks; Multi-Layer Perceptron; Back Propagation

Journal:

IJECCE

Volume:

6

Number:

2

Pages:

306-309

Month:

March