Full Text:   <1718>

Summary:  <1372>

CLC number: TP391.4; S758

On-line Access: 2016-08-05

Received: 2016-04-14

Revision Accepted: 2016-07-14

Crosschecked: 2016-07-26

Cited: 0

Clicked: 4583

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Wen-long Song

http://orcid.org/0000-0001-9729-7602

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.8 P.741-749

http://doi.org/10.1631/FITEE.1601169


Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography


Author(s):  Jia-yin Song, Wen-long Song, Jian-ping Huang, Liang-kuan Zhu

Affiliation(s):  College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China

Corresponding email(s):   songjy@nefu.edu.cn, wls139@126.com

Key Words:  Fisheye lens, Least squares method, Image segmentation, Ecology in image processing, Hemispherical photography


Jia-yin Song, Wen-long Song, Jian-ping Huang, Liang-kuan Zhu. Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(8): 741-749.

@article{title="Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography",
author="Jia-yin Song, Wen-long Song, Jian-ping Huang, Liang-kuan Zhu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="8",
pages="741-749",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601169"
}

%0 Journal Article
%T Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography
%A Jia-yin Song
%A Wen-long Song
%A Jian-ping Huang
%A Liang-kuan Zhu
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 8
%P 741-749
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601169

TY - JOUR
T1 - Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography
A1 - Jia-yin Song
A1 - Wen-long Song
A1 - Jian-ping Huang
A1 - Liang-kuan Zhu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 8
SP - 741
EP - 749
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601169


Abstract: 
Analysis of forest canopy hemisphere images is one of the most important methods for measuring forest canopy structure parameters. In this study, our main focus was on using circular image region segmentation, which is the basis of forest canopy hemispherical photography. The boundary of a forest canopy hemisphere image was analyzed via histogram, rectangle, and Fourier descriptors. The image boundary characteristics were defined and obtained based on the following: (1) an edge model that contains three parts, i.e., step, ramp, and roof; (2) boundary points of discontinuity; (3) an edge that has a linear distribution of scattering points. On this basis, we proposed a segmentation method for the circular region in a forest canopy hemisphere image, fitting the circular boundary and computing the center and radius by the least squares method. The method was unrelated to the parameters of the image acquisition device. Hence, this study lays a foundation for automatically adjusting the parameters of high-performance image acquisition devices used in forest canopy hemispherical photography.

基于边界分析的森林冠层半球图像中心点定位与分割

概要:分析森林半球图像是测定森林冠层结构参数的重要方法之一。本文主要研究半球图像中圆形区域的分割方法,这是分析半球图像的基础。通过直方图、矩形度和傅里叶描述子进行森林半球图像边界的分析,得到边界特性如下:(1)边缘模型包含三种,分别是台阶、斜坡和屋顶边缘模型;(2)边界点离散;(3)边缘存在线性分布离散点。在此基础上我们提出了森林半球图像圆形区域的分割方法,拟合圆形边界线,同时用最小二乘法计算圆心点坐标及半径。该方法与获取图像的硬件设备参数无关,因此为引入参数自动调整的高性能设备获取森林半球图像奠定了基础。
关键词:鱼眼镜头;最小二乘法;图像分割;生态学图像处理;半球图像

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Ahmad, A., Xavier, J., Santos-Victor, J., et al., 2014. 3D to 2D bijection for spherical objects under equidistant fisheye projection. Comput. Vis. Image Understand., 125:172-183.

[2]Ahn, S.J., Rauh, W., Warnecke, H.J., 2001. Least-squares orthogonal distances fitting of circle, sphere, ellipse, hyperbola, and parabola. Patt. Recogn., 34(12):2283-2303.

[3]Bai, X., 2015. Morphological infrared image enhancement based on multi-scale sequential toggle operator using opening and closing as primitives. Infrared Phys. Technol., 68:143-151.

[4]Brusa, A., Bunker, D.E., 2014. Increasing the precision of canopy closure estimates from hemispherical photography: blue channel analysis and under-exposure. Agr. Forest Meteorol., 195-196:102-107.

[5]Chaudhuri, D., 2010. A simple least squares method for fitting of ellipses and circles depends on border points of a two-tone image and their 3-D extensions. Patt. Recogn. Lett., 31(9):818-829.

[6]de Marco, T., Cazzato, D., Leo, M., et al., 2015. Randomized circle detection with isophotes curvature analysis. Patt. Recogn., 48(2):411-421.

[7]Gonsamo, A., Pellikka, P., 2009. The computation of foliage clumping index using hemispherical photography. Agr. Forest Meteorol., 149(10):1781-1787.

[8]Huesca, M., García, M., Roth, K.L., et al., 2016. Canopy structural attributes derived from AVIRIS imaging spectroscopy data in a mixed broadleaf/conifer forest. Remote Sens. Environ., 182:208-226.

[9]Kanatani, K., Rangarajan, P., 2011. Hyper least squares fitting of circles and ellipses. Comput. Stat. Data Anal., 55(6):2197-2208.

[10]Kwak, K., Yoon, U., Lee, D.K., et al., 2013. Fully-automated approach to hippocampus segmentation using a graph-cuts algorithm combined with atlas-based segmentation and morphological opening. Magn. Reson. Imag., 31(7):1190-1196.

[11]Lan, J., Zeng, Y., 2013. Multi-threshold image segmentation using maximum fuzzy entropy based on a new 2D histogram. Optik Int. J. Light Electon Opt., 124(18):3756-3760.

[12]Liu, C., Kang, S., Li, F., et al., 2013. Canopy leaf area index for apple tree using hemispherical photography in arid region. Sci. Horticult., 164:610-615.

[13]Liu, Z., Wang, C., Chen, J.M., et al., 2015. Empirical models for tracing seasonal changes in leaf area index in deciduous broadleaf forests by digital hemispherical photography. Forest Ecol. Manag., 351:67-77.

[14]Mailly, D., Turbis, S., Chazdon, R.L., 2013. SOLARCALC 7.0: an enhanced version of a program for the analysis of hemispherical canopy photographs. Comput. Electron. Agr., 97:15-20.

[15]Nafis, U.K., Arya, K.V., Pattanaik, M., 2013. Histogram statistics based variance controlled adaptive threshold in anisotropic diffusion for low contrast image enhancement. Signal Process., 93(6):1684-1693.

[16]Neumann, H.H., den Hartog, G., 1989. Leaf area measurements based on hemispheric photographs and leaf-litter collection in a deciduous forest during autumn leaf-fall. Agr. Forest Meteorol., 45(3-4):325-345.

[17]Schneider, D., Schwalbe, E., Maas, H.G., 2009. Validation of geometric models for fisheye lenses. ISPRS J. Photogr. Remote Sens., 64(3):259-266.

[18]Scitovski, R., Marošević, T., 2015. Multiple circle detection based on center-based clustering. Patt. Recogn. Lett., 52:9-16.

[19]Sharma, R.C., Kajiwara, K., Honda, Y., 2013. Estimation of forest canopy structural parameters using kernel-driven bi-directional reflectance model based multi-angular vegetation indices. ISPRS J. Photogr. Remote Sens., 78:50-57.

[20]Woodgate, W., Armston, J.D., Disney, M., et al., 2016. Quantifying the impact of woody material on leaf area index estimation from hemispherical photography using 3D canopy simulations. Agr. Forest Meteorol., 226-227:1-12.

[21]Yao, Z., Yi, W., 2016. Curvature aided Hough transform for circle detection. Exp. Syst. Appl., 51:26-33.

[22]Yuan, B., Liu, M., 2015. Power histogram for circle detection on images. Patt. Recogn., 48(10):3268-3280.

[23]Zhang, H., Wiklund, K., Andersson, M., 2016. A fast and robust circle detection method using isosceles triangles sampling. Patt. Recogn., 54:218-228.

[24]Zhao, D., Lv, M., Wang, P., et al., 2014. Can the plant area index of a submerged vegetation canopy be estimated using digital hemispherical photography? Agr. Forest Meteorol., 192-193:69-77.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2022 Journal of Zhejiang University-SCIENCE