Anisotropic Diffusion Based Weed Classifier

摘要：

This paper presents a new approach of anisotropic diffusion to classify the weed images into broad and narrow class for real time selective herbicide application The classifier we proposed based on Perona and Malik equation. Its low computational complexity and fast runtimes makes this method well suited for real-time vision applications. The developed system has been tested on weeds in the lab; the results show a very reliable performance and drastically less computational effort on images of weeds taken under varying field conditions. The analysis of the results shows over 97.6％ classification accuracy over 200 sample images.

关键词： Image Processing Anisotropic Diffusion Realtime Recognition Ecology Weed detection

作者: Shujaat Ali Khan Abdul Muhamin Naeem Owais Adnan Attaullah Khan

作者单位: Institute of Management Sciences Peshawar, Pakistan ITC&S, NetSol Technologies Peshawar, Pakistan Provincial Assembly Secretariat, NWFP Peshawar, Pakistan

会议类型: 国际会议

会议名称: 2010 International Conference on Educational and Network Technology(2010教育与网络技术国际会议 ICENT 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 11-15

在线出版日期: 2010-06-25（万方平台首次上网日期，不代表论文的发表时间）