Research on tree species identification algorithm based on combination of leaf traditional characteristics and distance matrix as well as corner matrix

CHEN Ming-jian; CHEN Zhi-bo; YANG Meng; MO Qin

doi:10.13332/j.1000-1522.20160351

Journal of Beijing Forestry University > 2017 > 39(2): 108-116. > DOI: 10.13332/j.1000-1522.20160351

CHEN Ming-jian, CHEN Zhi-bo, YANG Meng, MO Qin. Research on tree species identification algorithm based on combination of leaf traditional characteristics and distance matrix as well as corner matrix[J]. Journal of Beijing Forestry University, 2017, 39(2): 108-116. DOI: 10.13332/j.1000-1522.20160351

Citation:

PDF (2648 KB)

Research on tree species identification algorithm based on combination of leaf traditional characteristics and distance matrix as well as corner matrix

College of Information, Beijing Forestry University, Beijing, 100083, P. R. China

More Information

Received Date: October 26, 2016
Revised Date: December 20, 2016
Published Date: January 31, 2017

Graphical Abstract

Abstract

Abstract

Aiming at the problem of tree species identification based on leaf characteristics, this paper self-defines two leaf outline characteristics of leaf angle and edge angle mean on the basis of 25 kinds of characteristics such as leaf texture, invariant moments and traditional shapes, regards the definition and inference of similar polygon as theoretical basis and proposes a kind of classification method for tree species identification which is to construct distance matrix and corner matrix based on leaf outline. Firstly, the tree leaf image was pre-processed to extract the normalized leaf feature vector. Then KNN was used to choose the top 20 of the highest similarity result set. And then distance matrix and corner matrix were constructed to identify and match more accurately. During pre-processing, in order to obtain more accurate characteristics of leaf outline, this paper designs an image preprocessing algorithm of eliminating leaf shadow by taking advantage of significant differences between saturation and chromaticity in HSV color space. During identification and matching, this paper uses the Douglas Peucker approximation algorithm to extract the approximate polygon of leaf outline, and defines calculation methods of distance matrix, corner matrix, matrix element similarity, matrix similarity and comprehensive similarity, and designs a kind of algorithm combining global matching and local matching. The algorithm had been implemented and run on Android mobile phone platform. Results showed that the accuracy of the algorithm was 99.61% among 1 907 complete samples of 32 categories and 94.92% among 851 incomplete samples of 32 categories in Flavia dataset. In Leafsnap dataset, the accuracy of the algorithm was 98.26% of top 5 among 23 147 Lab samples of 185 categories. Compared with other algorithms, this kind of algorithm had higher identification accuracy, better description ability for leaf outline, better robust performance for incomplete leaf, twisted leaf and shadowed leaf, and better practicability and adaptability.
- tree species identification,
- distance matrix,
- corner matrix,
- dynamic programming,
- leaf outline

FullText(HTML)

References (23)

References

[1]	王丽君, 淮永建, 彭月橙.基于叶片图像多特征融合的观叶植物种类识别[J].北京林业大学学报, 2015, 37(1):55-61. doi: 10.13332/j.cnki.jbfu.2015.01.006 WANG L J, HUAI Y J, PENG Y C.Follow-leaf plant species identification based on multi-feature fusion of leaf images[J]. Journal of Beijing Forestry University, 2015, 37(1):55-61. doi: 10.13332/j.cnki.jbfu.2015.01.006
[2]	袁津生, 姚宇飞.基于分形维度的叶片图像识别方法[J].计算机工程与设计, 2012, 33(2):670-673. doi: 10.3969/j.issn.1000-7024.2012.02.050 YUAN J S, YAO Y F.Face image recognition method based on fractal dimension[J]. Computer Engineering and Design, 2012, 33(2): 670-673. doi: 10.3969/j.issn.1000-7024.2012.02.050
[3]	YAHIAOUI I, MZOUGHI O, BOUJEMAA N. Leaf shape descriptor for tree species identification[C]//2012 IEEE International Conference on Multimedia and Expo. Amsterdam: IEEE, 2012: 254-259. https: //www.researchgate.net/publication/261125339_Leaf_Shape_Descriptor_for_Tree_Species_Identification
[4]	李洋, 李岳阳, 罗海驰, 等.基于形状特征的植物叶片在线识别方法[J].计算机工程与应用, 2017, 53(2):162-165. doi: 10.3778/j.issn.1002-8331.1504-0233 LI Y, LI Y Y, LUO H C, et al. On-line identification method of plant leaf based on shape feature[J]. Computer Engineering and Applications, 2017, 53(2):162-165. doi: 10.3778/j.issn.1002-8331.1504-0233
[5]	SATTI V, SATYA A, SHARMA S. An automatic leaf recognition system for plant identification using machine vision technology[J]. International Journal of Engineering Science and Technology, 2013, 5(4): 874-879. http://d.old.wanfangdata.com.cn/OAPaper/oai_doaj-articles_83ccc22bcf4760049fb096a6365da736
[6]	BACKES A R, CASANOVA D, BRUNO O M. Plant leaf identification based on volumetric fractal dimension[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2009, 23(6): 1145-1160. doi: 10.1142/S0218001409007508
[7]	谢莉, 成运, 曾接贤, 等.基于颜色和梯度方向共生直方图的图像检索[J].计算机工程与应用, 2016, 52(10):181-186. doi: 10.3778/j.issn.1002-8331.1406-0366 XIE L, CHENG Y, ZENG J X, et al. Image retrieval based on color and gradient directional symbiotic histogram[J]. Computer Engineering and Applications, 2016, 52(10):181-186. doi: 10.3778/j.issn.1002-8331.1406-0366
[8]	MALLAH C, COPE J, ORWELL J. Plant leaf classification using probabilistic integration of shape, texture and margin features[J/OL].[2014-01-06]. http://www.actapress.com/Abstract.aspx?paperId=455022.
[9]	WANG X F, HUANG DS, DU J X, et al. Classification of plant leaf images with complicated background[J]. Applied Mathematics & Computation, 2008, 205(2):916-926. https://www.sciencedirect.com/science/article/abs/pii/S0096300308003718
[10]	NOVOTNY P, SUK T. Leaf recognition of woody species in Central Europe[J]. Biosystems Engineering, 2013, 115(4): 444-452. doi: 10.1016/j.biosystemseng.2013.04.007
[11]	LE T L, NGUYEN Q K, PHAM N H. Leaf based plant identification system for android using surf features in combination with bag of words model and supervised learning[C]//2013 International Conference on Advanced Technologies for Communications (ATC 2013). Ho Chi Minh City: IEEE, 2013: 404-407. https: //www.researchgate.net/publication/259644407_Leaf_based_plant_identification_system_for_Android_using_SURF_features_in_combination_with_Bag_of_Words_model_and_supervised_learning
[12]	SUMATHI C S, KUMAR A V S. Neural network based plant identification using leaf characteristics fusion[J]. International Journal of Computer Applications, 2014, 89(5):31-35. doi: 10.5120/15499-4141
[13]	刘念, 阚江明.基于多特征融合和深度信念网络的植物叶片识别[J].北京林业大学学报, 2016, 38(3):110-119. http://d.old.wanfangdata.com.cn/Periodical/bjlydxxb201603014 LIU N, KAN J M. Establishment of plant leaf based on multi-feature fusion and depth-of-concept network[J]. Journal of Beijing Forestry University, 2016, 38(3): 110-119. http://d.old.wanfangdata.com.cn/Periodical/bjlydxxb201603014
[14]	SHAYAN H, SAJEEVAN G. Plant recognition from leaf image through artificial neural network[J]. International Journal of Computer Applications, 2013, 62(17):15-18. doi: 10.5120/10172-4897
[15]	HU R X, JIA W, LING H B, et al. Multiscale distance matrix for fast plant leaf recognition[J]. IEEE transactions on image processing, 2012, 21(11): 4667-4672. doi: 10.1109/TIP.2012.2207391
[16]	GWO C Y, WEI C H. Plant identification through images: using feature extraction of key points on leaf contours1[J]. Applications in Plant Sciences, 2013, 1(11):1-9 http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM25202493
[17]	KUMAR N, BELHUMENR P N, BISWAS A, et al. Leafsnap: a computer vision system for automatic plant species identification[EB/OL].[2016-08-20]. http://neerajkumar.org/base/papers/nk_eccv2012_leafsnap.pdf.
[18]	董红霞, 郭斯羽.一种结合形状与纹理特征的植物叶片分类方法[J].计算机工程与应用, 2014, 50(23):185-188. doi: 10.3778/j.issn.1002-8331.1301-0138 DONG H X, GUO S Y. Classification of plant leaf based on shape and texture features[J]. Computer Engineering and Applications, 2014, 50 (23): 185-188. doi: 10.3778/j.issn.1002-8331.1301-0138
[19]	朱黎辉, 李晓宁.基于多特征组合的球形果蔬智能分选方法[J].计算机工程与应用, 2016, 52(5):173-178. doi: 10.3778/j.issn.1002-8331.1403-0280 ZHU L H, LI X N.Intelligent sorting method of spherical fruits and vegetables based on multi-feature combination[J]. Computer Engineering and Applications, 2016, 52(5): 173-178. doi: 10.3778/j.issn.1002-8331.1403-0280
[20]	VISVALINGAM M, WHYATT D. Line generalisation by repeated elimination of points[J]. The Cartographic Journal, 1993, 30(1):46-51. doi: 10.1179/caj.1993.30.1.46
[21]	曾接贤, 刘秀朋, 符祥.角点距离矩阵和同心圆划分的曲线描述与匹配[J].中国图象图形学报, 2012, 17(8):1011-1020. http://d.old.wanfangdata.com.cn/Periodical/zgtxtxxb-a201208016 ZENG J X, LIU X P, FU X. Curve description and matching of corner distance matrix and concentric circle partition[J]. Chinese Journal of Image and Graphics, 2012, 17(8): 1011-1020. http://d.old.wanfangdata.com.cn/Periodical/zgtxtxxb-a201208016
[22]	WU S G, BAO F S, XU E Y, et al. A leaf recognition algorithm for plant classification using probabilistic neural network[C]//2007 IEEE International Symposium on Signal Processing and Information Technology.Cairo: IEEE, 2007: 11-16. http: //www.oalib.com/paper/4021582
[23]	WU S G, BAO F S, XU E Y, et al. A leaf recognition algorithm for plant classification using PNN (probabilistic neural network)[EB/OL].[2016-09-10]. http://flavia.sourceforge.net/.

[1]	Sun Yanan, Liu Yajing, Sun Zhao, Luo Mi, Zhang Yungen, Sun Yujun. Radial growth of Cunninghamia lanceolata and its response to climate in Jiangle National Forest Farm, Fujian Province of eastern China[J]. Journal of Beijing Forestry University, 2024, 46(2): 18-27. DOI: 10.12171/j.1000-1522.20220373
[2]	Liu Siqi, Man Xiuling, Zhang Di, Xu Zhipeng. Dynamics of root decomposition and carbon and nitrogen release of four tree species with different diameter classes in the cold temperate zone[J]. Journal of Beijing Forestry University, 2023, 45(7): 36-46. DOI: 10.12171/j.1000-1522.20210490
[3]	Fan Xiaoyun, Guo Sujuan, Li Yanhua. Quality difference analysis and climate adaptability evaluation of Chinese chestnut in different ecological regions[J]. Journal of Beijing Forestry University, 2022, 44(11): 20-30. DOI: 10.12171/j.1000-1522.20210289
[4]	Yang Xin, Wang Jianjun, Du Zhi, Wang Wenwen, Meng Jinghui. Development of individual-tree diameter increment model for natural Larix gmelinii forests based on climatic factors[J]. Journal of Beijing Forestry University, 2022, 44(8): 1-11. DOI: 10.12171/j.1000-1522.20210353
[5]	Tang Yan, Zhao Runan, Ren Gang, Cao Fuliang, Zhu Zunling. Prediction of potential distribution of Lycium chinense based on MaxEnt model and analysis of its important influencing factors[J]. Journal of Beijing Forestry University, 2021, 43(6): 23-32. DOI: 10.12171/j.1000-1522.20200103
[6]	Huang Ruizhi, Yu Tao, Zhao Hui, Zhang Shengkai, Jing Yang, Li Junqing. Prediction of suitable distribution area of the endangered plant Acer catalpifolium under the background of climate change in China[J]. Journal of Beijing Forestry University, 2021, 43(5): 33-43. DOI: 10.12171/j.1000-1522.20200254
[7]	TAO Fa-qiang, GAO Lu-shuang, WANG Xiao-ming. Determination and climatic response of growth release/inhibition of diecious species[J]. Journal of Beijing Forestry University, 2015, 37(3): 111-117. DOI: 10.13332/j.1000-1522.20140307
[8]	GAO Lu-shuang, WANG Xiao-ming, ZHAO Xiu-hai.. Growth response of two coexisting species to climate change in broadleaved Korean pine forests in Changbai Mountain, northeastern China.[J]. Journal of Beijing Forestry University, 2013, 35(3): 24-31.
[9]	LIU Chun-yan, , GU Jian-cai, LI Ji-yue, CHEN Ping, LU Gu i-qiao, TIAN Guo-heng. Correlated analysis between the growth of Larix principisrupprechtii and climatic factors in Saihanba Nature Reserve, northern Hebei Province．[J]. Journal of Beijing Forestry University, 2009, 31(4): 102-105.
[10]	HUANG Rong-feng, FURUKAWA Ikuo, BAO Fu-cheng, ZHAO You-ke. Response of tree-ring structure of poplar to climate factors in the Mu Us Desert[J]. Journal of Beijing Forestry University, 2005, 27(3): 24-29.

Cited By

Cited by

Periodical cited type(2)

1.	魏裕沛，郭娟，殷亚方. 树木木质部含碳率变化规律研究进展. 世界林业研究. 2024(03): 60-66 .
2.	尚超，徐霞，鲍莉荣，周婷婷. 装配式建筑生命周期碳平衡BIM模型仿真. 计算机仿真. 2023(04): 267-271 .

Other cited types(1)

Get Citation

PDF

XML

Article views (1676) PDF downloads (19) Cited by(3)

Turn off MathJax

Article Contents

Abstract

References

Research on tree species identification algorithm based on combination of leaf traditional characteristics and distance matrix as well as corner matrix