我们的网站为什么显示成这样?

可能因为您的浏览器不支持样式,您可以更新您的浏览器到最新版本,以获取对此功能的支持,访问下面的网站,获取关于浏览器的信息:

|Table of Contents|

基于直觉模糊集的阔叶树苗叶片边缘检测(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2014年06期
Page:
77-80
Column:
研究论文
publishdate:
2014-12-09

Article Info:/Info

Title:
Edge detection of hardwood seedlings leaves based on intuitionistic fuzzy set
Article ID:
1000-2006(2014)06-0077-04
Author(s):
HU Chunhua1LI Pingping2
1.College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037,China;
2.College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037,China
Keywords:
hardwood seedlings leaves leaf edge detection intuitionist fuzzy set
Classification number :
TP24
DOI:
10.3969/j.issn.1000-2006.2014.06.015
Document Code:
A
Abstract:
In this paper, a novel edge detection method based on intuitionistic fuzzy set(IFS)for hardwood seedlings leaves is proposed to accurately segment the leaves from images in complex background. Firstly, 3×3 templates of the x-direction, y direction, the direction of 45° and 135° were utilized to cluster the R, G, and B gray image respectively. Secondly, the maximum variance method was proposed to extract the fuzzy clustering image threshold. Finally, image edge was detected according to the threshold, where a clear boundary was obtained. Proposed method performed better than classical edge detection methods of differential operator. Experiments for kinds of hardwood seedlings were carried out, and the results indicated that the proposed method was effectiveness to detect the leaf edge, especially for the overlap region.

References

[1] 李先锋,朱伟兴,纪滨,等. 基于图像处理和蚁群优化的形状特征选择与杂草识别[J].农业工程学报,2010,26(10):178-182. Li X F, Zhu W X,Ji B, et al. Shape feature selection and weed recognition based on image processing and ant colony optimization [J]. Transactions of the CSAE, 2010,26(10):178-182.
[2] 胡春华,李萍萍. 基于图像处理的黄瓜缺氮与缺镁判别的研究[J]. 江苏大学学报:自然科学版,2004, 25(S1):9-12. Hu C H, Li P P. Application of image processing to diagnose cucumbers short of Mg and N[J]. Journal of Jiangsu University:National Science Edition, 2004, 25(S1):9-12.
[3] 李寒,王库,边昊一. 基于Mean-shift 和提升小波变换的棉花叶片边缘的图像检测[J].农业工程学报,2010,26(S1):182-186. Li H, Wang K, Bian H Y. Cotton leaf image edge detection using Mean-shift algorithm and lifting wavelet transform [J]. Transactions of the CSAE, 2010, 26(S1): 182-186.
[4] 张辉,马明建. 基于改进Sobel 算法的叶片图像边缘检测[J].农机化研究,2012(5):46-49. Zhang H,Ma M J. An blade edge detection method based improved sobel operator [J]. Agricultural Mechanization Research, 2012(5):46-49.
[5] Zheng L Y,Zhang J T,Wang Q Y. Mean-shift-based color segmentation of images containing green vegetation [J]. Computer and Electronics in Agriculture,2009,65(1): 93-98.
[6] Lopez-Molina C,De Baets B,Bustince H. Generating fuzzy edge images from gradient magnitudes [J]. Computer Vision and Image Understanding,2011,115(11): 1571-1580.
[7] 林开颜,司慧萍, 周强,等. 基于模糊逻辑的植物叶片边缘检测方法[J]. 农业机械学报,2013,44(6):227-231. Lin K Y, Si H P, Zhou Q, et al. Plant leaf edge detection based on fuzzy logic[J]. Tansactions of the Chinese Society for Agricultural Machinery, 2013, 44(6):227-231.
[8] Rafael C Gonzalez, Richard E Woods. Digital Image Processing [M]. 2rd edition. New Jersey, USA: Pearson Education, 2008.
[9] Zadeh L A. Fuzzy sets [J]. Information and Control, 1965, 8(3):338-353.
[10] Alshennawy A A, Aly A A. Edge detection in digital images using fuzzy logic technique[J]. World Academy of Science, Engineering and Technology, 2009, 51: 178-186..
[11] Aijaz Ur Rahman khan, Kavita Thakur. An efficient fuzzy logic based edge detection algorithm for gray scale image [J]. International Journal of Emerging Technology and Advanced Engineering, 2012, 2(8):245-250.
[12] Atanassov K. Intuitionistic fuzzy sets [J]. Fuzzy Sets and Systems, 1986, 20(1): 87-96.
[13] Atanassov K, Pasi G, Yager R R. Intuitionistic fuzzy interpretations of multi-criteria multi-person and multi-measurement tool decision making [J]. International Journal of Systems Science, 2005, 36(14):859-868.
[14] Tamalika Chaira. A rank ordered filter for medical image edge enhancement and detection using intuitionistic fuzzy set [J]. Applied Soft Computing, 2012, 12(4):1259-1266.
[15] Tamalika Chaira, Ray A K. A new measure using intuitionistic fuzzy set theory and its application to edge detection [J]. Applied Soft Computing, 2008, 8(2): 919-927.
[16] Mehmet Sezgin, Bülent Sanku. Survey over image thresholding techniques and quantitative performance evaluation [J]. Journal of Electronic Imaging, 2004, 13(1):146-165.

Last Update: 2014-12-31