2D In Situ Method for Measuring Plant Leaf Area with Camera Correction and Background Color Calibration
Author(s) -
Li-fen Tu,
Qi Peng,
Chunsheng Li,
Aiqun Zhang
Publication year - 2021
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2021/6650099
Subject(s) - calibration , computer science , adaptability , distortion (music) , measure (data warehouse) , computer vision , artificial intelligence , block (permutation group theory) , algorithm , mathematics , ecology , amplifier , computer network , statistics , geometry , bandwidth (computing) , database , biology
In order to measure the plant leaf area conveniently and quickly in an indoor laboratory and outdoor field, a set of scaffold leaf area measurement systems was designed and manufactured. A 2D in situ method for measuring plant leaf area with camera correction and background color calibration was proposed. The method integrates three subalgorithms: fast calibration and distortion correction algorithm, background color calibration algorithm, and edge error correction algorithm. At the same time, the Visual Studio 2015 and OpenCV 3.4.0 were used to develop and test the algorithm. In order to verify the measurement speed and environmental adaptability of the system, the test was carried out in the complex light disturbance outdoors, and the results were consistent with those in the room. In order to verify the measurement accuracy of the system, this method was used to measure the standard rectangular gauge block of known area and the real leaf area, respectively, and its data were compared with the data measured by Wanshen LA-S plant image analyzer. The results show that both methods have a good stability, and the algorithm proposed in this paper performs better in measurement accuracy and environmental adaptability.
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