Affiliation:
1. Shanxi Normal University
2. XiJing University
Abstract
Crop disease leaf image segmentation is a key step in crop disease recognition. In the paper, a segmentation method of crop disease leaf image is proposed to segment leaf image with non-uniform illumination based on maximum entropy and genetic algorithm (GA). The information entropy is regarded as the fitness function of GA, the maximum entropy as convergence criterion of GA. After genetic operation, the optimal threshold is obtained to segment the image of disease leaf. The experimental results of the maize disease leaf image show that the proposed method can select the threshold automatically and efficiently, and has an advantage over the other three algorithms, and also can reserve the main spot features of the original disease leaf image.
Publisher
Trans Tech Publications, Ltd.
Reference9 articles.
1. Piyush Chaudhary, Anand K. Chaudhari, Dr. A. N. Cheeran and Sharda Godara. Color Transform Based Approach for Disease Spot Detection on Plant Leaf. International Journal of Computer Science and Telecommunications, 2012, 3(6), 65-70.
2. Song Kai, liu zhikun, Su hang, Guo chunhong, A Research of Maize Disease Image Recognition of Corn Based on BP Networks. Third International Conference on Measuring Technology and Mechatronics Automation, 2011, 246-249.
3. Diao Zhihua, Song Yinmao, Wang Huan, Wang Yunpeng. Study on the research summary of plant spot segmentation. Agricultural Mechanization Research, 2012(10): 1-5.
4. Valliammal N., Geethalakshmi S.N. A Novel Approach for Plant Leaf Image Segmentation using Fuzzy Clustering. International Journal of Computer Applications, 2012, 44(3), 10-20.
5. Helly M. E., Rafea A., Salwa-El-Gammal. An integrated image processing system for leaf disease detection and diagnosis. in Proc. IICAI, 2003, 1182-1195.
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献