Maize seeds varieties identification based on multi-object feature extraction and optimized neural network

In order to apply machine vision technology replacing human vision to identify maize seed varieties in a real-time, objective, accurate and non-invasive procedure, the hardware and software systems to identify the seeds of maize need to be developed. For maize seed and characteristics of the seed images, the identification technology of maize seed varieties and algorithms has studied and explored in depth. A multi-object features extraction and the optimized neural network using PCA identification method adapting to maize seeds varieties identification was proposed. Geometric features and color features parameters of maize seeds were extracted. Maize seeds image processing strategies and varieties identification algorithms, which was based on the machine vision, was optimized. The precision and speed of maize seeds varieties identification was improved. Through maize seeds varieties identification test on four species including Nongda 108, Ludan 981, Zhengdan 958 and Wuyue 18, average identification time-consuming of each seed was 0.127 s, and integrated identification accuracy was more than 97%. Research shows that identification and detection of maize seeds varieties based on machine vision is feasible, and this method can improve the efficiency and correct identification rate of maize seed varieties.