Feature extraction based on visual invariance and species identification of weed seeds

In order to study the biological stability?genetic characteristics of seeds, a method of feature extraction was presented based on visual invariance. The paper analyzed the morphological characteristics and the Hu’s invariant moments, and extracted 16 features of weed seeds on the basis of the analysis. These features could effectively represent the weed seeds of biological stability?genetic characteristics. Experiment results showed that the extracted 16 features with visual invariant which were taken as Back Propagation (BP) neural network identification and classification of the feature sets could quickly identify the weed seeds with a high recognition rate. Therefore, the method is important in the plant quarantine and agricultural production.