An Image Recognition Method Based on Ant Colony Optimization Neural Network Using in Imaging Fuze

摘要：

　　Target image recognition is an important issue in the information processing of imaging fuse system.In the paper,the main frame is proposed which can solve the problem of target image recognition and many computer simulation experiments are carried out.A recognition algorithm based on ant colony optimization and neural network is proposed.It overcomes the shortcomings of traditional BP algorithm and converges fast.The results of experiments prove that the presented algorithm can shorten the training time effectively and increase the accuracy of recognition,so it is very useful in improving the effective destroying ability of the missile.

关键词： pattern recognition target recognition neural network feature extraction ant colony optimization

作者: Keyong Wang Shikai Xing

作者单位: School of Continuing Education, Beijing Institute of Technology, Beijing 100081, China School of Vocational Technique, Hebei Normal University, Shijiazhuang 050024, China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 1886-1890

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）