Estimating Tomato Plant Leaf Area Using Multiple Images from Different Viewing Angles

• Published in: Journal of advanced computational intelligence and intelligent informatics Vol. 28; no. 2; pp. 352 - 360
• Main Authors: Yamaguchi, Nobuhiko, Okumura, Hiroshi, Fukuda, Osamu, Yeoh, Wen Liang, Tanaka, Munehiro
• Format: Journal Article
• Language: English
• Published: Tokyo Fuji Technology Press Co. Ltd 01.03.2024
• Subjects: Estimation; Methods; Test sets; Tomatoes; Viewing
• ISSN: 1343-0130; 1883-8014
• DOI: 10.20965/jaciii.2024.p0352

The estimation of leaf area is an important measure for understanding the growth, development, and productivity of tomato plants. In this study, we focused on the leaf area of a potted tomato plant and proposed methods, namely, NP, D 2 , and D 3 , for estimating its leaf area. In the NP method, we used multiple tomato plant images from different viewing angles to reduce the estimation error of the leaf area, whereas in the D 2 and D 3 methods, we further compensated for the perspective effects. The performances of the proposed methods were experimentally assessed using 40 “Momotaro Peace” tomato plants. The experimental results confirmed that the NP method had a smaller mean absolute percentage error (MAPE) on the test set than the conventional estimation method that uses a single tomato plant image. Likewise, the D 2 and D 3 methods had a smaller MAPE on the test set than the conventional method that did not compensate for perspective effects.