Research Article | OPEN ACCESS
Method of Fruit Image Segmentation by Improved K-Means
Fangzheng Wang
Yancheng Institute of Health Sciences, Yancheng 224005, China
Advance Journal of Food Science and Technology` 2016 11:838-840
Received: May 25, 2015 | Accepted: June 22, 2015 | Published: April 15, 2016
Abstract
The clustering algorithm of K-means is a widely used clustering algorithm, which characteristic is efficient and simple to implement. In this study, it takes the clustering algorithm of K-means as the starting point, which also explains the improvement of the clustering algorithm of K-means clustering, discussing the application of K-means on the realization of fruit image segmentation.
Keywords:
Clustering algorithm, fruit image segmentation, K-means,
References
-
Cai, J., X. Zhou and Y. Li, 2008. Recognition of mature oranges in natural scene based on machine vision. T. Chinese Soc. Agric. Eng., 24: 175-178.
-
Chen, K., X. Zou, J. Xiong et al., 2013. Improved fruit fuzzy clustering image segmentation algorithm based on visual saliency. T. Chinese Soc. Agric. Eng., 29: 157-165.
-
Song, H., C. Zhang, J. Pan, X. Yin and Y. Zhuang, 2013. Segmentation and reconstruction of overlapped apple images based on convex hull. T. Chinese Soc. Agric. Eng., 29: 163-168.
-
Wang, X., X. Han and H. Mao, 2012. Vision-based detection of tomato main stem in greenhouse with red rope. T. Chinese Soc. Agric. Eng., 28: 135-141.
-
Zhou, W., J. Feng, G. Liu and X. Ma, 2013. Application of image registration technology in apple harvest robot. T. Chinese Soc. Agric. Eng., 29: 20-26.
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
|
ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
|
Information |
|
|
|
Sales & Services |
|
|
|