Crop row detection based on wavelet transformation and Otsu segmentation algorithm

被引：0
|
作者：
Han Y. [1 ]
Wang Y. [1 ]
Sun Q. [1 ]
Zhao Y. [2 ]
机构：
[1] Department of Electronics and Informatics, Zhejiang Sci-Tech University, Hangzhou
[2] Department of Mechanic, Zhejiang Sci-Tech University, Hangzhou
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2016年 / 38卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Agriculture navigation; Crop rows; Otsu; Wavelet transformation;
D O I：
10.11999/JEIT150421
中图分类号：
学科分类号：
摘要：
Vision-based agricultural vehicle navigation has become a popular research area of automated guidance, however, crop row detection in high weeds field is still a challenging topic. An image segmentation method mainly based on frequency and color information is proposed to remove weeds. The algorithm is based on total frequency parameters, more total crop frequency, alternation regular of crop rows, Otsu method and color model transformation. The total frequency parameters are obtained from wavelet multi-resolution decomposition. The least square method is used in fitting straight line to detect the crop rows. Experiments show that the algorithm can effectively overcome the high weeds. The average processing time of a single 480×640 pixels image is 132 ms. © 2016, Science Press. All right reserved.
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页码：63 / 70
页数：7
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