Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area

Shengjian Ma; Jian Wang; Junxian Guo

doi:doi:10.11648/j.eas.20240906.11

Research Article |

| Peer-Reviewed

Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area

Shengjian Ma^*, Jian Wang, Junxian Guo

Published in Engineering and Applied Sciences (Volume 9, Issue 6)

Received: 9 October 2024 Accepted: 25 October 2024 Published: 12 November 2024

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.

Published in	Engineering and Applied Sciences (Volume 9, Issue 6)
DOI	10.11648/j.eas.20240906.11
Page(s)	129-135
Creative Commons	This is an Open Access article, 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 or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Image Processing, Plant Leaf Area, Contour Extraction, Lesion Area Calculation, Edge Detection

References

[1]	Zhao Hongdan, Tian Xiping. Research on threshold determination method for segmenting remote sensing image based on K-means algorithm [J]. Science Technology and Engineering, 2017, 17(09): 250-254.
[2]	Y. Yu, X. Yu, Z. Zhao, K. Qian and D. Wang. Image Analysis System for Optimal Geometric Distribution of RFID Tags Based on Flood Fill and DLT. IEEE Transactions on Instrumentation and Measurement [J]. Optik, 2018, 67: 839-848.
[3]	An, N., Palmer, C. M., Baker, R. L., Markelz, R. J. C., Ta, J., Covington, M. F., Weinig, C. Plant high-throughput phenotyping using photogrammetry and imaging techniques to measure leaf length and rosette area [J]. Computers and Electronics in Agriculture, 2016, 127: 376–394.
[4]	An, N., Welch, S. M., Markelz, R. J. C., Baker, R. L., Palmer, C. M., Ta, J., Weinig, C. Quantifying time-series of leaf morphology using 2D and 3D photogrammetry methods for high-throughput plant phenotyping [J]. Computers and Electronics in Agriculture, 2017, 135: 222–232.
[5]	Lee, U., Chang, S., Putra, G. A., Kim, H., & Kim, D. H. An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis [J]. PLOS ONE, 2018,, 13(4),: e0196615.
[6]	Müller-Linow, Mark, Wilhelm J, Briese C, et al. Plant Screen Mobile: an open-source mobile device app for plant trait analysis [J]. Plant Methods, 2019, 15(1).
[7]	Kenta Itakura, Fumiki Hosoi. Estimation of Leaf Inclination Angle in Three-Dimensional Plant Images Obtained from Lidar [J]. Remote sensing, 2019, 24(1): 24-34.
[8]	Zhang Jianli, Sun Shenshen, Qin Shuqi. Ore Image Segmentation Based on Optimal Threshold Segmentation of Genetic Algorithm [J]. Science Technology and Engineering, 2019, 19(07): 105-109.
[9]	Shaik KB, Ganesan P, Kalist V, Sathish BS, Jenitha JMM. Comparative Study of Skin Color Detection and Segmentation in HSV and YCbCr Color Space [J]. Procedia Comput Sci. 2015, 57: 41–48.
[10]	Ali, Mahdi M., Ahmed Al-Ani, Derek Eamus, Daniel K. Y. Tan. A new image-processing-based technique for measuring leaf dimensions [J]. American-Eurasian Journal of Agriculture & Environmental Science. 2012.12,: 1588-1594.
[11]	Sun Ying, He Guojin. High-resolution remote sensing image segmentation method based on labeled watershed algorithm [J]. Science Technology and Engineering, 2008, 43(11): 2776-2781.
[12]	N. R. Kasu and C. Saravanan. Segmentation on Chest Radiographs Using Otsu's and K-Means Clustering Methods [J]. International Conference on Inventive Research in Computing Applications (ICIRCA), 2018: 210-213.
[13]	Esmael Hamuda, Brian Mc Ginley, Martin Glavin. Edward Jones. Automatic crop detection under field conditions using the HSV colour space and morphological operations. Computers and Electronics in Agriculture [J]. Computers and Electronics in Agriculture, 2017, 133: 97-107.
[14]	Shanwen Zhang, Haoxiang Wang, Wenzhun Huang, Zhuhong You. Plant diseased leaf segmentation and recognition by fusion of superpixel, K-means and PHOG [J]. Optik. 2018, 157: 866-872.
[15]	Ole Mathis Opstad Kruse, José Manuel Prats-Montalbán, Ulf Geir Indahl, Knut Kvaal, Alberto Ferrer. Cecilia Marie Futsaether. Pixel classification methods for identifying and quantifying leaf surface injury from digital images [J]. Computers and Electronics in Agriculture. 2014, 108: 155-165.
[16]	Zhang Wu, Huang Shuai, Wang Jingjing, Liu Lianzhong. A segmentation method for wheat leaf images with disease in complex background [J]. Computer Engineering and Science. 2015, 37(07): 1349-1354.
[17]	Caldas L. S, Bravo C, Piccolo H, et al. Measurement of leaf area with a hand-scanner linked to a microcomputer [J]. Revista Brasileira de Fisiologia Vegetal, 1999, 4(1): 17-20.
[18]	C. Igathinathan, et al. Interactive computer software development for leaf areameasurement [J]. Computers and electronics in agriculture, 2006, 3(5): 403-415.
[19]	Hassan Hajjdiab, Abdellatif Obaid. A Vision-based Approach for Nondestructive Leaf Area Estimation [J]. Environmental Science and Information ApplicationTechnology, 2010, (2): 53-56S.
[20]	Chen Taotao, Chi Daocai, Liang Xi. Measurement method of multi leaf area based on geometric correction of rectangular frame [J]. Journal of agricultural engineering. 2012(08): 206-213.
[21]	Chen Ding Cai, Wang Dingcheng, Zha Jinshui. Research on the measurement method of real blade area based on machine vision [J]. Computer application, 2006 (05): 1226-1228.
[22]	Hariadi, Tony K; Fadholi, Zulfan; Chamim, Anna N N; Utama, Nafi A. Development of Leaf Area Meter Using OpenCV for Smartphone Application [J]. TELKOMNIKA., 2018, 16(4),: 1857-1863.

Cite This Article

Plain Text BibTeX RIS

APA Style

Ma, S., Wang, J., Guo, J. (2024). Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area. Engineering and Applied Sciences, 9(6), 129-135. https://doi.org/10.11648/j.eas.20240906.11

Copy | Download

ACS Style

Ma, S.; Wang, J.; Guo, J. Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area. Eng. Appl. Sci. 2024, 9(6), 129-135. doi: 10.11648/j.eas.20240906.11

Copy | Download

AMA Style

Ma S, Wang J, Guo J. Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area. Eng Appl Sci. 2024;9(6):129-135. doi: 10.11648/j.eas.20240906.11

Copy | Download

@article{10.11648/j.eas.20240906.11,
  author = {Shengjian Ma and Jian Wang and Junxian Guo},
  title = {Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area
},
  journal = {Engineering and Applied Sciences},
  volume = {9},
  number = {6},
  pages = {129-135},
  doi = {10.11648/j.eas.20240906.11},
  url = {https://doi.org/10.11648/j.eas.20240906.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20240906.11},
  abstract = {In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area

AU  - Shengjian Ma
AU  - Jian Wang
AU  - Junxian Guo
Y1  - 2024/11/12
PY  - 2024
N1  - https://doi.org/10.11648/j.eas.20240906.11
DO  - 10.11648/j.eas.20240906.11
T2  - Engineering and Applied Sciences
JF  - Engineering and Applied Sciences
JO  - Engineering and Applied Sciences
SP  - 129
EP  - 135
PB  - Science Publishing Group
SN  - 2575-1468
UR  - https://doi.org/10.11648/j.eas.20240906.11
AB  - In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.

VL  - 9
IS  - 6
ER  -

Copy | Download

Author Information

Shengjian Ma

College of Life Science and Technology, Lingnan Normal University, Zhanjiang, China

Contact Email
Jian Wang

College of Life Science and Technology, Lingnan Normal University, Zhanjiang, China; Mechanical and Electrical Engineering College, Xinjiang Agricultural University, Urumqi, China
Junxian Guo

Mechanical and Electrical Engineering College, Xinjiang Agricultural University, Urumqi, China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Ma, S., Wang, J., Guo, J. (2024). Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area. Engineering and Applied Sciences, 9(6), 129-135. https://doi.org/10.11648/j.eas.20240906.11

Copy | Download

ACS Style

Ma, S.; Wang, J.; Guo, J. Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area. Eng. Appl. Sci. 2024, 9(6), 129-135. doi: 10.11648/j.eas.20240906.11

Copy | Download

AMA Style

Ma S, Wang J, Guo J. Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area. Eng Appl Sci. 2024;9(6):129-135. doi: 10.11648/j.eas.20240906.11

Copy | Download

@article{10.11648/j.eas.20240906.11,
  author = {Shengjian Ma and Jian Wang and Junxian Guo},
  title = {Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area
},
  journal = {Engineering and Applied Sciences},
  volume = {9},
  number = {6},
  pages = {129-135},
  doi = {10.11648/j.eas.20240906.11},
  url = {https://doi.org/10.11648/j.eas.20240906.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20240906.11},
  abstract = {In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area

AU  - Shengjian Ma
AU  - Jian Wang
AU  - Junxian Guo
Y1  - 2024/11/12
PY  - 2024
N1  - https://doi.org/10.11648/j.eas.20240906.11
DO  - 10.11648/j.eas.20240906.11
T2  - Engineering and Applied Sciences
JF  - Engineering and Applied Sciences
JO  - Engineering and Applied Sciences
SP  - 129
EP  - 135
PB  - Science Publishing Group
SN  - 2575-1468
UR  - https://doi.org/10.11648/j.eas.20240906.11
AB  - In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.

VL  - 9
IS  - 6
ER  -

Copy | Download