Coverage Estimation on Stellera chamaejasme L. Based on Digital Photos
Received date: 2009-03-26
Revised date: 2009-04-30
Online published: 2009-07-10
The coverage of stellera was estimated based on the digital images. The excess green operator was chosen to classify green and non-green vegetation. The stellera flowers were automatically extracted from non-green vegetation using brightness feature and area threshold. The holes in the flowers were filled using run length marking algorithm. Ten photos were randomly selected for evaluating the classification precision and the Kappa coefficient was 0.80. The excess green was not sensitive between stellera leaves and grass. The precision can improve when the hue feature is used to discriminate the stellera leaves under the HLS color space. The regression analysis was carried out and the linear equation could express the relationship best between the stellera flower areas and leaves areas. The regression simulation method can get higher estimation precision of the stellera leaves.
Key words： Stellera chamaejasme L.; Excess green; Hole filling; Kappa coefficient
QIAN Jin-Bei . Coverage Estimation on Stellera chamaejasme L. Based on Digital Photos[J]. Advances in Earth Science, 2009 , 24(7) : 776 -783 . DOI: 10.11867/j.issn.1001-8166.2009.07.0776
[1] Liu Ying, Long Ruijun, Yao Tuo. Research progress on Stelleta chamaejasme L. in grassland[J].Pratacultural Science,2004,21(6):55-61.[刘英,龙瑞军,姚拓.草地狼毒研究进展[J].草业科学,2004,21(6):55-61.]
[2] Casady G M，Hanley R S，Seelan S K. Detection of leafy spurge（Euphorbia esula）using multidate high-resolution satellite imagery[J].Weed Technology,2005,19:462-467.
[3] Underwood E，Ustin S，DiPietro D. Mapping nonnative plants using hyperspectral imagery[J].Remote Sensing of Environment,2003, 86:150-161.
[4] Lawrence R L，Wood S D，Sheley R L. Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications（RandomForest）[J].Remote Sensing of Environment,2006, 100:356-362.
[5] Zhang Yunxia, Li Xiaobing, Chen Yunhao. Overview of field and multi-scale remote sensing measurement approaches to grassland vegetation coverage[J].Advances in Earth Science, 2003,18(1):85-93.[张云霞,李晓兵,陈云浩.草地植被盖度的多尺度遥感与实地测量方法综述[J].地球科学进展,2003,18(1):85-93.]
[6] Li Cunjun, Wang Jihua, Liu Liangyun, et al. Automated digital image analyses for estimating percent ground percent ground cover of winter wheat based on object features[J].Journal of Zhejiang University (Agriculture & Life Sciences), 2004, 30(6):650-656.[李存军,王纪华,刘良云,等.基于数字照片特征的小麦覆盖度自动提取研究[J].浙江大学学报:农业与生命科学版,2004,30(6):650-656.]
[7] Mao Wenhua. Study on Infield Weed Detection Using Machine Vision[D].Beijing: China Agricultural University,2004.[毛文华.基于机器视觉的田间杂草识别技术研究[D].北京：中国农业大学,2004.]
[8] Li Decai, Kong Fanrong, Ma Mingji. A survey on the toxic plant in the pastureland of the Qilian country[J].Qinghai Prataculture,2003, 12(2):41-42.[李德才,孔繁荣,马明继.祁连县草地毒草调查报告[J].青海草业,2003,12(2):41-42.]
[9] Long Mansheng. Weed identification from corn seedling based on computer vision[J].Transactions of the SCAE,2007, 23(7):139-144.[龙满生. 玉米苗期杂草的计算机识别技术研究[J]. 农业工程学报, 2007, 23(7):139-144.][10] Zhou Tianjuan, Zhang Tiezhong, Yang Li. Study on strawberry harvesting robot: Ⅲ Application of scan line filling algorithm in vacancy filling of strawberry image[J].Journal of China Agricultural University,2007, 12(2):67-71.[周天娟, 张铁中, 杨丽. 草莓采摘机器人的研究: Ⅲ 扫描线填充算法在草莓图像孔洞填充中的应用[J]. 中国农业大学学报,2007, 12(2):67-71.]
[11] Li Wenbin, Wang Changsong. Hole filling algorithm based on conturs information[J].Computer Engineering and Design, 2008, 29(15):3 958-3 959,3 962.[李文斌, 王长松. 基于边界信息的孔洞填充算法[J]. 计算机工程与设计, 2008, 29(15):3 958-3 959,3 962.]
/
| 〈 |
|
〉 |
甘公网安备62010202000687
