Feature Selection of Corn Seed Based on Genetic Algorithm and Support Vector Machine

摘要：

Studying on corn breed identification based on digital image of the corn seed, it is significant to find out new valuable features for improving recognition rate of corn breed. This paper adopts the algorithm of genetic algorithm (GA) combined with Support Vector Machine (SVM) to optimizing the features of corn seed. During optimizing process, New features which have greater contributions to recognition are found out from the color and shape features of white part (embryo department) and yellow part (coronal department) of corn seed.

关键词： Genetic algorithm Support Vector Machine Feature selection Corn seed

作者: CHENG Hong PANG Li Xin

作者单位: College of Information Science and Technology, Agriculture University of Hebei, China Modern Education and Technology Centre, Agriculture University of Hebei, Baoding, China, 071001

会议类型: 国际会议

会议名称: 2008 International Conference on IAEA(2008农业信息化、自动化与电气化国际会议)

会议地点: 镇江

会议语种:英文

页码: 494-499

在线出版日期: 2008-11-01（万方平台首次上网日期，不代表论文的发表时间）