江苏大学学报（自然科学版）2011，Vol.32Issue(6)：621-625,5.DOI:10.3969/j.issn.1671-7775.2011.06.001
基于BP神经网络的玉米单倍体种子图像分割
Image segmentation of maize haploid seeds based on BP neural network
摘要
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.关键词
玉米种子/单倍体/BP神经网络/图像分割/种子分选Key words
corn seeds/haploid/BP neural network/image segmentation/seed sorting分类
信息技术与安全科学引用本文复制引用
张俊雄,吴科斌,宋鹏,李伟,陈绍江..基于BP神经网络的玉米单倍体种子图像分割[J].江苏大学学报（自然科学版）,2011,32(6):621-625,5.基金项目
国家"863"高技术研究发展计划项目(2010AA101401) （2010AA101401）
国家自然科学基金资助项目(31071320) （31071320）
