Image Based Estimation of Fruit Phytopathogenic Lesions Area

被引：0

作者：

Marcal, Andre R. S. ^{[1
,2
]}

Santos, Elisabete M. D. S. ^{[2
]}

Tavares, Fernando ^{[1
,3
]}

机构：

[1] Univ Porto, Fac Ciencias, Porto, Portugal

[2] INESC TEC, Porto, Portugal

[3] Univ Porto, CIBIO Ctr Invest Biodiversidade & Recursos Genet, Lab Associado, InBIO, Vairao, Portugal

来源：

PATTERN RECOGNITION AND IMAGE ANALYSIS, IBPRIA 2019, PT II | 2019年 / 11868卷

关键词：

Fruit phytopathogenic lesion; 3D modeling; Spheroid; Volume; Surface area; SURFACE-AREA; VOLUME;

D O I：

10.1007/978-3-030-31321-0_25

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A method was developed to measure the surface area of walnut fruit phytopathogenic lesions from images acquired with a basic calibration target. The fruit is modelled by a spheroid, established from the 2D view ellipse using an iterative process. The method was tested with images of colour circular marks placed on a wooden spheroid. It proved effective in the estimation of the spheroid semi-diameters (average relative errors of 0.8% and 1.0%), spheroid surface (1.77%) and volume (2.71%). The computation of the colour mark surface area was within the expected error, considering the image resolution (up to about 4%), for 22 out of 28 images tested.

引用

页码：285 / 295

页数：11

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