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Image Segmentation of Field Rape Based on Template Matching and K-means Clustering

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成果类型:
期刊论文
作者:
Dujuan Shuai;Changhua Liu;Xiaoming Wu;Hao Li;Fugui Zhang
通讯作者:
Liu, C.
作者机构:
School of Math and Computer, Wuhan Polytechnic University, Wuhan, 430023, China
Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, 430062, China
通讯机构:
School of Math and Computer, Wuhan Polytechnic University, Wuhan, China
语种:
英文
期刊:
IOP Conference Series: Materials Science and Engineering
ISSN:
1757-8981
年:
2018
卷:
466
期:
1
页码:
012118
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
Giving that the changing light in the natural condition has negative impacts on the image segmentation of rape fields, the image of rape was processed by template match algorithm and K-means clustering algorithm to extract the rape flowers. In order to achieve the accurately segmentation of the rape flowers, firstly, creating a template library and using the template matching algorithm to locate the target area of the test image. Then, the processed image will be convert to LAB color space, and using K-means clustering algorithm to classify acc...

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