Digital Image Sensor-Based Assessment of the Status of Oat (Avena sativa L.) Crops after Frost Damage

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Macedo Cruz, Antonia and Pajares Martinsanz, Gonzalo and Santos, Matilde and Villegas Romero, Isidro (2011) Digital Image Sensor-Based Assessment of the Status of Oat (Avena sativa L.) Crops after Frost Damage. Sensors, 11 (6). pp. 6015-6036. ISSN 1424-8220

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Official URL: https://doi.org/10.3390/s110606015




Abstract

The aim of this paper is to classify the land covered with oat crops, and the quantification of frost damage on oats, while plants are still in the flowering stage. The images are taken by a digital colour camera CCD-based sensor. Unsupervised classification methods are applied because the plants present different spectral signatures, depending on two main factors: illumination and the affected state. The colour space used in this application is CIELab, based on the decomposition of the colour in three channels, because it is the closest to human colour perception. The histogram of each channel is successively split into regions by thresholding. The best threshold to be applied is automatically obtained as a combination of three thresholding strategies: (a) Otsu’s method, (b) Isodata algorithm, and (c) Fuzzy thresholding. The fusion of these automatic thresholding techniques and the design of the classification strategy are some of the main findings of the paper, which allows an estimation of the damages and a prediction of the oat production.


Item Type:Article
Uncontrolled Keywords:digital image sensor; agricultural images; unsupervised classification; automatic thresholding; CIELab colour space; fuzzy error matrix; oat frost damage
Subjects:Sciences > Computer science > Artificial intelligence
ID Code:68462
Deposited On:02 Nov 2021 12:34
Last Modified:03 Nov 2021 12:17

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