Growth stage identification for cherry tomato using image processing techniques
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Conference Proceeding
Source Title
2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)
Publication Date
2020
Abstract
Controlled environment agriculture are being developed with the purpose of increasing production yield in farms. For optimal yield, it is very important to have an understanding about the relationship of environmental factors such as radiation, temperature, nutrients, water, and in relation with the growth state of the crop. Growth monitoring of cherry tomato crops in traditional methods are extremely labor-intensive, destructive, and costly in terms of time and money. Thus, application of computer vision has become an area of interest in the study of monitoring tomatoes’ growth. In this study, image processing techniques are employed to identify the growth stage of cherry tomato as fruiting, flowering, and leafing stage. Confusion matrix with True Positive rate and False negative rate, and ROC are used to evaluate the decision support system developed. Experimental results show a high performance in determining the growth stage of test cherry tomato images.
html
Recommended Citation
Loresco, P., Valenzuela, I., Gamara, R., Obien, J., & Dadios, E. P. (2020). Growth stage identification for cherry tomato using image processing techniques. 2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/15344
Disciplines
Computer Engineering
Keywords
Image processing—Digital techniques; Tomatoes—Growth—Monitoring
Upload File
wf_no
