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| Image segmentation of maize haploid seeds based on BP neural network |
| 1.College of Engineering, China Agricultural University, Beijing 100083, China; 2.National Maize Improvement Center of China, Beijing 100094, China) |
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Abstract Based on BP neural network of maize haploid seeds，an image segmentation method was proposed to research 1050-37 corn with genetic marks. According to color features，corn seed images were divided into three color patterns of purple area, yellow area and white area. Different color features of normalized rgb and HSV color space were analyzed, and 7 features were chosen as input parameters to establish a BP neural network model with 3 layers to achieve effective image segmentation of maize haploid seeds. The experiments show that the classification accuracies of the model are 97.61% for purple marks area, 93.34% for yellow area and 94.09% for white area，respectively. The purple marks area acquired by BP NN is effective and reliable for the identification of haploid kernels and hybrid kernels.
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2011, Vol. 32 
