ArticleSensors (Basel, Switzerland)2019
A Plant Leaf Geometric Parameter Measurement System Based on the Android Platform.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Leaf Analyzer: A fully automated and open-source tool for high-throughput leaf trait measurement.Plant phenomics (Washington, D.C.) · 2026Article
- Deep learning-based automatic diagnosis of rice leaf diseases using ensemble CNN models.Scientific reports · 2025Article
- Article
- Accelerating leaf area measurement using a volumetric approach.Plant methods · 2022Article
- Leaf Area Calculation Models for Vines Based on Foliar Descriptors.Plants (Basel, Switzerland) · 2021Article
- Automatic Diagnosis of Rice Diseases Using Deep Learning.Frontiers in plant science · 2021Article
- Detection of Performance of Hybrid Rice Pot-Tray Sowing Utilizing Machine Vision and Machine Learning Approach.Sensors (Basel, Switzerland) · 2019Article
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Authors and funding
8 authors.
Funding
Abstract
Automatic and efficient plant leaf geometry parameter measurement offers useful information for plant management. The objective of this study was to develop an efficient and effective leaf geometry parameter measurement system based on the Android phone platform. The Android mobile phone was used to process and measure geometric parameters of the leaf, such as length, width, perimeter, and area. First, initial leaf images were pre-processed by some image algorithms, then distortion calibration was proposed to eliminate image distortion. Next, a method for calculating leaf parameters by using the positive circumscribed rectangle of the leaf as a reference object was proposed to improve the measurement accuracy. The results demonstrated that the test distances from 235 to 260 mm and angles from 0 to 45 degrees had little influence on the leafs' geometric parameters. Both lab and outdoor measurements of leaf parameters showed that the developed method and the standard method were highly correlated. In addition, for the same leaf, the results of different mobile phone measurements were not significantly different. The leaf geometry parameter measurement system based on the Android phone platform used for this study could produce high accuracy measurements for leaf geometry parameters.
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Registered trials
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