关键词: 籽棉, 图像特征, 反向传播神经网络, 分级

Abstract: In order to improve the accuracy and objectivity of classification of seed cotton, the paper presented a grading model. The model was based on image features and used BP neural networks as the classification algorithm. According to GB1103-2007 national standards of seed cotton, white degree, yellow degree and impurity degree were extracted as characteristic parameters. The BP neural networks were trained with part of the samples. After completion of the training, the left samples were substituted into the trained networks, and the result showed that classification precision of the model was 81%. The experimental results show that this model can promote grading accuracy and objectivity.

Key words: seed cotton, image feature, BP neural network, grading